test_data.json 618 KB
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[{"pk": 1, "model": "workflows.connection", "fields": {"output": 1, "workflow": 1, "input": 5}}, {"pk": 2, "model": "workflows.connection", "fields": {"output": 2, "workflow": 1, "input": 6}}, {"pk": 3, "model": "workflows.connection", "fields": {"output": 3, "workflow": 1, "input": 7}}, {"pk": 4, "model": "workflows.connection", "fields": {"output": 4, "workflow": 1, "input": 8}}, {"pk": 5, "model": "workflows.connection", "fields": {"output": 10, "workflow": 4, "input": 16}}, {"pk": 6, "model": "workflows.connection", "fields": {"output": 10, "workflow": 4, "input": 17}}, {"pk": 7, "model": "workflows.connection", "fields": {"output": 12, "workflow": 4, "input": 15}}, {"pk": 8, "model": "workflows.connection", "fields": {"output": 8, "workflow": 3, "input": 14}}, {"pk": 9, "model": "workflows.connection", "fields": {"output": 11, "workflow": 3, "input": 13}}, {"pk": 10, "model": "workflows.connection", "fields": {"output": 6, "workflow": 2, "input": 12}}, {"pk": 11, "model": "workflows.connection", "fields": {"output": 9, "workflow": 2, "input": 11}}, {"pk": 12, "model": "workflows.connection", "fields": {"output": 5, "workflow": 1, "input": 10}}, {"pk": 13, "model": "workflows.connection", "fields": {"output": 18, "workflow": 5, "input": 22}}, {"pk": 14, "model": "workflows.connection", "fields": {"output": 19, "workflow": 5, "input": 26}}, {"pk": 15, "model": "workflows.connection", "fields": {"output": 20, "workflow": 5, "input": 27}}, {"pk": 16, "model": "workflows.connection", "fields": {"output": 17, "workflow": 5, "input": 18}}, {"pk": 17, "model": "workflows.connection", "fields": {"output": 20, "workflow": 5, "input": 19}}, {"pk": 18, "model": "workflows.connection", "fields": {"output": 18, "workflow": 5, "input": 20}}, {"pk": 19, "model": "workflows.connection", "fields": {"output": 13, "workflow": 6, "input": 29}}, {"pk": 20, "model": "workflows.connection", "fields": {"output": 14, "workflow": 6, "input": 30}}, {"pk": 21, "model": "workflows.connection", "fields": {"output": 15, "workflow": 6, "input": 31}}, {"pk": 22, "model": "workflows.connection", "fields": {"output": 21, "workflow": 6, "input": 21}}, {"pk": 1, "model": "workflows.abstractinput", "fields": {"widget": 1, "name": "String", "short_name": "str", "uid": "0f6fa6df-b8d1-4e12-a9ac-427233bb090a", "default": "", "required": false, "multi": false, "parameter_type": "textarea", "variable": "string", "parameter": true, "order": 0, "description": ""}}, {"pk": 2, "model": "workflows.abstractinput", "fields": {"widget": 2, "name": "object", "short_name": "obj", "uid": "3a319eaf-52fb-4cd0-b1b6-78d8a807b892", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "object", "parameter": false, "order": 0, "description": ""}}, {"pk": 6, "model": "workflows.abstractinput", "fields": {"widget": 5, "name": "Delimiter", "short_name": "del", "uid": "8862cfd6-6444-46b7-9b16-456f27b58cb4", "default": "", "required": false, "multi": false, 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"multi": true, "parameter_type": null, "variable": "elements", "parameter": false, "order": 0, "description": ""}}, {"pk": 18, "model": "workflows.abstractinput", "fields": {"widget": 10, "name": "String", "short_name": "str", "uid": "c658923a-a611-414b-ba7e-510aaa83ff19", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "string", "parameter": false, "order": 0, "description": ""}}, {"pk": 19, "model": "workflows.abstractinput", "fields": {"widget": 11, "name": "Time", "short_name": "tim", "uid": "1a463ddc-289a-4250-ae41-9f7a3eb81881", "default": "10", "required": false, "multi": false, "parameter_type": "text", "variable": "time", "parameter": true, "order": 0, "description": "Time in seconds"}}, {"pk": 20, "model": "workflows.abstractinput", "fields": {"widget": 11, "name": "Data", "short_name": "dat", "uid": "c6ddfb2b-a04a-448e-a853-8b4e13d4ccdf", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "data", "parameter": false, "order": 0, "description": ""}}, {"pk": 21, "model": "workflows.abstractinput", "fields": {"widget": 12, "name": "pickled object", "short_name": "obj", "uid": "1d6e265c-22e1-4761-a9a2-5615f00528b0", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "pickled_object", "parameter": false, "order": 0, "description": ""}}, {"pk": 22, "model": "workflows.abstractinput", "fields": {"widget": 13, "name": "file", "short_name": "fil", "uid": "2de6ce93-0063-4770-a1d1-93fc2d98bccc", "default": "", "required": true, "multi": false, "parameter_type": "file", "variable": "file", "parameter": true, "order": 0, "description": ""}}, {"pk": 23, "model": "workflows.abstractinput", "fields": {"widget": 14, "name": "Type your integer", "short_name": "int", "uid": "1e52e44e-94cc-4666-8278-04da49d8f890", "default": "", "required": true, "multi": false, "parameter_type": "text", "variable": "integer", "parameter": true, "order": 0, "description": ""}}, {"pk": 25, "model": "workflows.abstractinput", "fields": {"widget": 16, "name": "Range Length (Number of Items in Range)", "short_name": "rln", "uid": "4f60c95a-3177-4a5d-b047-75d971ee7654", "default": "10", "required": false, "multi": false, "parameter_type": "text", "variable": "n_range", "parameter": true, "order": 0, "description": ""}}, {"pk": 26, "model": "workflows.abstractinput", "fields": {"widget": 17, "name": "Object", "short_name": "obj", "uid": "175cd7ae-46dd-471e-9aa2-29105cb077eb", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "object", "parameter": false, "order": 0, "description": "Any type of object."}}, {"pk": 30, "model": "workflows.abstractinput", "fields": {"widget": 21, "name": "Integer 2", "short_name": "int", "uid": "10fdef7a-7c55-464d-bd7d-1e273759eda9", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "integer2", "parameter": false, "order": 0, "description": ""}}, {"pk": 31, "model": 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"7ab35883-9bb7-477b-a367-6c6ac95edc75", "default": "", "required": true, "multi": true, "parameter_type": null, "variable": "data_inds", "parameter": false, "order": 0, "description": ""}}, {"pk": 40, "model": "workflows.abstractinput", "fields": {"widget": 26, "name": "Ensemble Type", "short_name": "ent", "uid": "d07ef228-561f-49d0-8ea5-5e4638d14b76", "default": "consensus", "required": true, "multi": false, "parameter_type": "select", "variable": "ens_type", "parameter": true, "order": 0, "description": ""}}, {"pk": 41, "model": "workflows.abstractinput", "fields": {"widget": 27, "name": "Integer List", "short_name": "int", "uid": "aa8cdbe8-041b-455e-b03c-30d662f34c7b", "default": "", "required": false, "multi": true, "parameter_type": null, "variable": "integer", "parameter": false, "order": 0, "description": ""}}, {"pk": 42, "model": "workflows.abstractinput", "fields": {"widget": 28, "name": "Integer 2", "short_name": "int", "uid": "0bd80a21-e628-48c6-b3d8-58e8121e4711", 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"variable": "file", "parameter": false, "order": 0, "description": ""}}, {"pk": 48, "model": "workflows.abstractinput", "fields": {"widget": 32, "name": "File", "short_name": "fil", "uid": "d2b094de-d94c-4a7c-acbe-c21e5042183f", "default": "", "required": false, "multi": false, "parameter_type": "file", "variable": "file", "parameter": true, "order": 0, "description": ""}}, {"pk": 3, "model": "workflows.abstractinput", "fields": {"widget": 3, "name": "String", "short_name": "str", "uid": "21652a75-6742-4330-9bc3-9683f30a5618", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "string", "parameter": false, "order": 1, "description": ""}}, {"pk": 5, "model": "workflows.abstractinput", "fields": {"widget": 4, "name": "Triplet graph", "short_name": "tri", "uid": "d0826218-2d76-47a3-aa68-a884ea552c9d", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "triplets", "parameter": false, "order": 1, "description": ""}}, {"pk": 9, "model": "workflows.abstractinput", "fields": {"widget": 7, "name": "Name", "short_name": "nam", "uid": "01af240a-0a52-4c7d-9c82-9ac1bd0982d8", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "name", "parameter": false, "order": 1, "description": ""}}, {"pk": 10, "model": "workflows.abstractinput", "fields": {"widget": 7, "name": "Precision", "short_name": "pre", "uid": "119a7253-5c19-468a-82b7-91b95fdecf36", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "precision", "parameter": false, "order": 1, "description": ""}}, {"pk": 11, "model": "workflows.abstractinput", "fields": {"widget": 7, "name": "F score", "short_name": "f", "uid": "46771a73-77e1-40d1-9a53-1a4ffed49f21", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "fscore", "parameter": false, "order": 1, "description": ""}}, {"pk": 12, "model": "workflows.abstractinput", "fields": {"widget": 7, "name": 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"required": false, "multi": false, "parameter_type": null, "variable": "string", "parameter": false, "order": 1, "description": ""}}, {"pk": 28, "model": "workflows.abstractinput", "fields": {"widget": 19, "name": "File", "short_name": "fil", "uid": "9d55262f-eb97-423f-b875-2b8ab02e6f82", "default": "", "required": false, "multi": false, "parameter_type": "bigfile", "variable": "file", "parameter": true, "order": 1, "description": ""}}, {"pk": 29, "model": "workflows.abstractinput", "fields": {"widget": 20, "name": "List", "short_name": "lst", "uid": "c35deb32-ca39-435a-b859-50e4c94a7c74", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "input_list", "parameter": false, "order": 1, "description": "Input list"}}, {"pk": 33, "model": "workflows.abstractinput", "fields": {"widget": 23, "name": "Dictionary 2", "short_name": "dct", "uid": "53efae34-3906-4732-818c-78f44e6bceea", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "dict2", "parameter": false, "order": 1, "description": ""}}, {"pk": 34, "model": "workflows.abstractinput", "fields": {"widget": 23, "name": "Dictionary 1", "short_name": "dct", "uid": "7d53195e-49f3-4873-989d-e096563f84ed", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "dict1", "parameter": false, "order": 1, "description": ""}}, {"pk": 45, "model": "workflows.abstractinput", "fields": {"widget": 30, "name": "Signal", "short_name": "sgn", "uid": "3d89935f-e3cb-4c7a-a941-abe5627fb1bc", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "signal", "parameter": false, "order": 1, "description": "Signal that triggers stopwatch."}}, {"pk": 49, "model": "workflows.abstractinput", "fields": {"widget": 33, "name": "Orange data table", "short_name": "odt", "uid": "41e34489-1835-4d16-88cf-fdfc355839de", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "data", "parameter": false, "order": 1, "description": "Orange data table"}}, {"pk": 50, "model": "workflows.abstractinput", "fields": {"widget": 34, "name": "DS Model", "short_name": "mdl", "uid": "aaa8d949-147c-4b5b-8b4e-fb23acf44ea9", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "model", "parameter": false, "order": 1, "description": "Decision Support model"}}, {"pk": 51, "model": "workflows.abstractinput", "fields": {"widget": 35, "name": "DS model", "short_name": "mdl", "uid": "1f13bb91-47fb-4ba6-bdee-2d96f05d6f45", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "model", "parameter": false, "order": 1, "description": "model"}}, {"pk": 52, "model": "workflows.abstractinput", "fields": {"widget": 36, "name": "Microarray csv data file", "short_name": "csv", "uid": "4a2fc0cc-4140-46a8-924c-72ffad6297e0", "default": "", "required": true, "multi": false, "parameter_type": "file", "variable": "file", "parameter": true, "order": 1, "description": ""}}, {"pk": 56, "model": "workflows.abstractinput", "fields": {"widget": 37, "name": "Distance metric", "short_name": "dm", "uid": "e04bd4bb-a2d2-4e56-b986-5d4e605c8786", "default": "1", "required": true, "multi": false, "parameter_type": "select", "variable": "metric", "parameter": true, "order": 1, "description": "Distance metric"}}, {"pk": 57, "model": "workflows.abstractinput", "fields": {"widget": 37, "name": "Data table", "short_name": "odt", "uid": "f3424ab8-e105-4887-885d-68144fc59e13", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "table", "parameter": false, "order": 1, "description": "Orange data table with examples"}}, {"pk": 58, "model": "workflows.abstractinput", "fields": {"widget": 38, "name": "Hierarchical clustering", "short_name": "hcl", "uid": "0ae6fa4f-9032-42f0-a65c-067b221036c6", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "hclustering", "parameter": false, "order": 1, "description": "Orange hierarchical clustering object"}}, {"pk": 59, "model": "workflows.abstractinput", "fields": {"widget": 39, "name": "SEGS set of rules", "short_name": "rls", "uid": "1e4ce1f5-f8f1-4f50-8ebf-5d230909e968", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "rules", "parameter": false, "order": 1, "description": "SEGS set of rules"}}, {"pk": 69, "model": "workflows.abstractinput", "fields": {"widget": 40, "name": "Input data", "short_name": "rnk", "uid": "b1ec20d6-2740-4de5-9e9a-598d00f25e24", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "inputData", "parameter": false, "order": 1, "description": "List of pairs (geneID, rank)"}}, {"pk": 77, "model": "workflows.abstractinput", "fields": {"widget": 41, "name": "Data table", "short_name": "odt", "uid": "2e913773-e48c-4401-b058-e75869eed9b6", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "ruletable", 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"required": true, "multi": false, "parameter_type": null, "variable": "training_dataset", "parameter": false, "order": 1, "description": "Define training dataset"}}, {"pk": 723, "model": "workflows.abstractinput", "fields": {"widget": 312, "name": "Fit model", "short_name": "fit", "uid": "bbceed4d-4b34-4491-961c-daad03749524", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "fitmodel_url", "parameter": false, "order": 1, "description": "Fit model URL."}}, {"pk": 724, "model": "workflows.abstractinput", "fields": {"widget": 313, "name": "Dataset", "short_name": "dst", "uid": "8618f799-6bfd-4852-8a2b-db34e4441235", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "dataset", "parameter": false, "order": 1, "description": ""}}, {"pk": 726, "model": "workflows.abstractinput", "fields": {"widget": 314, "name": "Fit Model", "short_name": "fit", "uid": "46e9a02d-a613-4a01-a8ee-51d578a32fea", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "fitmodel_url", "parameter": false, "order": 1, "description": "Fit Model URL"}}, {"pk": 730, "model": "workflows.abstractinput", "fields": {"widget": 315, "name": "Fit model", "short_name": "fit", "uid": "ab0969e7-bed6-4381-926f-ac5a16a77c08", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "fitmodel_url", "parameter": false, "order": 1, "description": "Fit model URL."}}, {"pk": 732, "model": "workflows.abstractinput", "fields": {"widget": 316, "name": "Fit Model", "short_name": "fit", "uid": "f1c72ba9-b59b-4fef-9fb8-ea2803f2c69c", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "fitmodel_url", "parameter": false, "order": 1, "description": "Fit Model URL"}}, {"pk": 733, "model": "workflows.abstractinput", "fields": {"widget": 317, "name": "Dataset", "short_name": "dst", "uid": "fa45f814-8206-4256-9964-451c88607b9f", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "dataset", "parameter": false, "order": 1, "description": ""}}, {"pk": 734, "model": "workflows.abstractinput", "fields": {"widget": 318, "name": "Dataset", "short_name": "dst", "uid": "d7e7f211-c4ec-4e2c-905c-81f18791e534", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "dataset", "parameter": false, "order": 1, "description": ""}}, {"pk": 735, "model": "workflows.abstractinput", "fields": {"widget": 319, "name": "query", "short_name": "str", "uid": "c7f7da84-266c-4fe2-8e08-84ffe7e7a126", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "query", "parameter": false, "order": 1, "description": ""}}, {"pk": 736, "model": "workflows.abstractinput", "fields": {"widget": 320, "name": "concept_net_json_response", "short_name": "jsn", "uid": "fc379a4b-e1d7-4a71-9d5d-7d7879ba6fc8", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "concept_net_json_response", "parameter": false, "order": 1, "description": "Conceptnet JSON response"}}, {"pk": 739, "model": "workflows.abstractinput", "fields": {"widget": 321, "name": "Limit", "short_name": "lmt", "uid": "594b1488-dadb-4c9e-9a73-4c2ebed10a9d", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "limit", "parameter": true, "order": 1, "description": "Input must be a number. This input influences how much results we want returned."}}, {"pk": 4, "model": "workflows.abstractinput", "fields": {"widget": 3, "name": "Filter", "short_name": "flt", "uid": "ccc080f1-e7e4-4bd7-9837-b59dc9037ae9", "default": "!classname", "required": false, "multi": false, "parameter_type": "text", "variable": "class", "parameter": true, "order": 2, "description": ""}}, {"pk": 46, "model": "workflows.abstractinput", "fields": {"widget": 30, "name": "Datetime", "short_name": "dt", "uid": "7d99a31a-af1f-4c9a-8487-28a24da85bf9", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "time_in", "parameter": false, "order": 2, "description": "Datetime, based on which the timespan is calcualted."}}, {"pk": 53, "model": "workflows.abstractinput", "fields": {"widget": 36, "name": "Fold change: Input data format", "short_name": "f", "uid": "94c5f4f1-7d85-45e2-8393-38fc31a70630", "default": "1", "required": true, "multi": false, "parameter_type": "select", "variable": "idf", "parameter": true, "order": 2, "description": "Specifies whether the input data is linear or log2 transformed (needed for fold change computation)."}}, {"pk": 55, "model": "workflows.abstractinput", "fields": {"widget": 37, "name": "Linkage", "short_name": "lin", "uid": "a08686eb-acef-47c1-8fca-6693ac142754", "default": "4", "required": true, "multi": false, "parameter_type": "select", "variable": "linkage", "parameter": true, "order": 2, "description": "Type of linkage"}}, {"pk": 64, "model": "workflows.abstractinput", "fields": {"widget": 40, "name": "Service wsdl location", "short_name": "loc", "uid": "3e20cd76-1532-48fe-9f01-841a8a8067f2", "default": "http://segs.ijs.si:8091/PlantSEGS?wsdl", "required": false, "multi": false, "parameter_type": "text", "variable": "wsdl", "parameter": true, "order": 2, "description": "Sevice wsdl location"}}, {"pk": 90, "model": "workflows.abstractinput", "fields": {"widget": 43, "name": "Service wsdl location", "short_name": "loc", "uid": "c749b077-fe34-440a-9f75-fde1326957d9", "default": "http://segs.ijs.si:8091/PlantSEGS?wsdl", "required": false, "multi": false, "parameter_type": "text", "variable": "wsdl", "parameter": true, "order": 2, "description": "Sevice wsdl location"}}, {"pk": 99, "model": "workflows.abstractinput", "fields": {"widget": 44, "name": "Fold change values", "short_name": "fc", "uid": "b66d62cd-ee76-4e31-9ed9-c09741a2b567", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "logfcs", "parameter": false, "order": 2, "description": "sorted list of pairs (geneID, logFC)"}}, {"pk": 103, "model": "workflows.abstractinput", "fields": {"widget": 45, "name": "Number of neighbours", "short_name": "k", "uid": "96947efb-4df1-48f8-8802-ac6bc2e1984b", "default": "10", "required": false, "multi": false, "parameter_type": "text", "variable": "k", "parameter": true, "order": 2, "description": ""}}, {"pk": 117, "model": "workflows.abstractinput", "fields": {"widget": 55, "name": "Database version", "short_name": "dbv", "uid": "ff783343-b1b5-4f43-9caa-1cfe35706e13", "default": "<latest>", "required": false, "multi": false, "parameter_type": "text", "variable": "databaseVersion", "parameter": true, "order": 2, "description": "Database version"}}, {"pk": 127, "model": "workflows.abstractinput", "fields": {"widget": 57, "name": "Service wsdl location", "short_name": "loc", "uid": "7a0ba606-a0de-4616-a8bc-600e03219fb7", "default": "http://segs.ijs.si:8090/SEGS?wsdl", "required": false, "multi": false, "parameter_type": "text", "variable": "wsdl", "parameter": true, "order": 2, "description": "Sevice wsdl location"}}, {"pk": 143, "model": "workflows.abstractinput", "fields": {"widget": 59, "name": "Database version", "short_name": "dbv", "uid": "fc0a5b03-f301-4e4a-b9d7-889d89467245", "default": "<latest>", "required": false, "multi": false, "parameter_type": "text", "variable": "databaseVersion", "parameter": true, "order": 2, "description": "Database version"}}, {"pk": 146, "model": "workflows.abstractinput", "fields": {"widget": 61, "name": "Database version", "short_name": "dbv", "uid": "29d6ed65-55b8-4d68-8d7a-c19c0e91fe35", "default": "<latest>", "required": false, "multi": false, "parameter_type": "text", "variable": "databaseVersion", "parameter": true, "order": 2, "description": "Database version"}}, {"pk": 150, "model": "workflows.abstractinput", "fields": {"widget": 62, "name": "Max nodes", "short_name": "mxn", "uid": "0fe196ff-1e7b-4047-917a-2d828f52f3ae", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "maxnodes", "parameter": true, "order": 2, "description": "Search parameter maxnodes"}}, {"pk": 156, "model": "workflows.abstractinput", "fields": {"widget": 66, "name": "SD Rules", "short_name": "rul", "uid": "ca5c3d62-8f8b-4cfd-9be2-200e5c5fd6fc", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "rules", "parameter": false, "order": 2, "description": "rules"}}, {"pk": 161, "model": "workflows.abstractinput", "fields": {"widget": 70, "name": "Input Table", "short_name": "tab", "uid": "07f782ce-6ad4-4eaa-bc4c-58a82e627335", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "inputTable", "parameter": false, "order": 2, "description": "Input Table as an Orange Table represented as a string"}}, {"pk": 165, "model": "workflows.abstractinput", "fields": {"widget": 71, "name": "Web service address", "short_name": "ws", "uid": "a9fc6cb8-53fe-4977-8c34-29347b274548", "default": "http://vihar.ijs.si:8099", "required": false, "multi": false, "parameter_type": "text", "variable": "wsdl", "parameter": true, "order": 2, "description": "Web service address"}}, {"pk": 168, "model": "workflows.abstractinput", "fields": {"widget": 72, "name": "Language", "short_name": "lng", "uid": "1f55805e-08de-4fe0-8bc9-3896da7cbcfd", "default": "en", "required": true, "multi": false, "parameter_type": "select", "variable": "lang", "parameter": true, "order": 2, "description": "Language of the input corpus"}}, {"pk": 181, "model": "workflows.abstractinput", "fields": {"widget": 73, "name": "Web service address", "short_name": "ws", "uid": "d717986e-e906-4599-bc07-0c772078dc8d", "default": "http://vihar.ijs.si:8099", "required": false, "multi": false, "parameter_type": "text", "variable": "wsdl", "parameter": true, "order": 2, "description": "Web service address"}}, {"pk": 186, "model": "workflows.abstractinput", "fields": {"widget": 74, "name": "Web service address", "short_name": "ws", "uid": "9d817240-a951-460e-84db-b46ae503cdfb", "default": "http://vihar.ijs.si:8099", "required": false, "multi": false, "parameter_type": "text", "variable": "wsdl", "parameter": true, "order": 2, "description": "Web service address"}}, {"pk": 188, "model": "workflows.abstractinput", "fields": {"widget": 75, "name": "Web service address", "short_name": "ws", "uid": "717b9e76-f0df-4f77-8edb-846f09226503", "default": "http://vihar.ijs.si:8099", "required": false, "multi": false, "parameter_type": "text", "variable": "wsdl", "parameter": true, "order": 2, "description": "Web service address"}}, {"pk": 194, "model": "workflows.abstractinput", "fields": {"widget": 78, "name": "Or input text", "short_name": "tex", "uid": "26773c28-d88a-4671-aa06-cb7f1aea1296", "default": "", "required": true, "multi": false, "parameter_type": "textarea", "variable": "text", "parameter": true, "order": 2, "description": "Input text"}}, {"pk": 196, "model": "workflows.abstractinput", "fields": {"widget": 80, "name": "File", "short_name": "fil", "uid": "096159a3-ddc8-4a57-b769-dddfb2590065", "default": "", "required": true, "multi": false, "parameter_type": "file", "variable": "file", "parameter": true, "order": 2, "description": "File"}}, {"pk": 199, "model": "workflows.abstractinput", "fields": {"widget": 81, "name": "Join Method", "short_name": "met", "uid": "27c8cd4a-1016-4a88-b463-4713874fc87f", "default": "union", "required": true, "multi": false, "parameter_type": "select", "variable": "method", "parameter": true, "order": 2, "description": ""}}, {"pk": 206, "model": "workflows.abstractinput", "fields": {"widget": 82, "name": "WSDL", "short_name": "ws", "uid": "c4b8b86a-13ac-4e87-8708-84cfb79cd24a", "default": "http://vihar.ijs.si:8095/totale?wsdl", "required": false, "multi": false, "parameter_type": "text", "variable": "wsdl", "parameter": true, "order": 2, "description": "Web service address"}}, {"pk": 213, "model": "workflows.abstractinput", "fields": {"widget": 83, "name": "mapping", "short_name": "map", "uid": "cd4ab84b-91c7-42ed-bbb2-66c4a2d36fe0", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "mapping", "parameter": false, "order": 2, "description": "mapping from ontology concepts to examples"}}, {"pk": 225, "model": "workflows.abstractinput", "fields": {"widget": 84, "name": "Dataset", "short_name": "dat", "uid": "f02b857e-cd78-4d09-bf5e-d58344963fb5", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "dataset", "parameter": false, "order": 2, "description": "Dataset in TreeLiker format"}}, {"pk": 230, "model": "workflows.abstractinput", "fields": {"widget": 85, "name": "Weighting Measure", "short_name": "wgh", "uid": "cc2a208c-bf6f-4f64-b51e-221c80366f8e", "default": "tfidf", "required": true, "multi": false, "parameter_type": "select", "variable": "weighting_measure", "parameter": true, "order": 2, "description": "Term Weighting Measure"}}, {"pk": 235, "model": "workflows.abstractinput", "fields": {"widget": 87, "name": "pos", "short_name": "pos", "uid": "03788382-f3b9-4580-8e85-b600874ef643", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "pos", "parameter": false, "order": 2, "description": "positive examples"}}, {"pk": 251, "model": "workflows.abstractinput", "fields": {"widget": 88, "name": "b", "short_name": "b", "uid": "746dac3a-bcf9-4546-b0cb-ccfea866707a", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "b", "parameter": false, "order": 2, "description": "background knowledge"}}, {"pk": 256, "model": "workflows.abstractinput", "fields": {"widget": 88, "name": "clauselength", "short_name": "cln", "uid": "d840e1d9-5bd1-4004-94ec-6acd5b3c9910", "default": "8", "required": false, "multi": false, "parameter_type": "text", "variable": "clauselength", "parameter": true, "order": 2, "description": "An integer specifying the maximum length of a feature\r\nbody."}}, {"pk": 259, "model": "workflows.abstractinput", "fields": {"widget": 89, "name": "Send empty strings to webservices", "short_name": "ses", "uid": "0efe46b1-f1f4-4811-aacf-5f97a23e925d", "default": "", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "sendemptystrings", "parameter": true, "order": 2, "description": ""}}, {"pk": 280, "model": "workflows.abstractinput", "fields": {"widget": 90, "name": "Send empty strings to webservices", "short_name": "ses", "uid": "4061b687-c92d-4eca-9e2a-b420bb2b8611", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "sendemptystrings", "parameter": true, "order": 2, "description": ""}}, {"pk": 287, "model": "workflows.abstractinput", "fields": {"widget": 91, "name": "Send empty strings to webservices", "short_name": "ses", "uid": "f5f83294-4688-4244-8b8a-95df71859fb0", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "sendemptystrings", "parameter": true, "order": 2, "description": ""}}, {"pk": 289, "model": "workflows.abstractinput", "fields": {"widget": 92, "name": "Attribute name", "short_name": "atr", "uid": "cbc6708b-6932-4858-8522-a7fa705af1fd", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "attr_name", "parameter": true, "order": 2, "description": "Attribute name to extract as list"}}, {"pk": 291, "model": "workflows.abstractinput", "fields": {"widget": 93, "name": "Send empty strings to webservices", "short_name": "ses", "uid": "527e1e1a-3ff7-40c1-add6-f08b84b82a2b", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "sendemptystrings", "parameter": true, "order": 2, "description": ""}}, {"pk": 293, "model": "workflows.abstractinput", "fields": {"widget": 94, "name": "Send empty strings to webservices", "short_name": "ses", "uid": "0161f92d-e191-4d60-979f-f0a7d69f40cb", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "sendemptystrings", "parameter": true, "order": 2, "description": ""}}, {"pk": 298, "model": "workflows.abstractinput", "fields": {"widget": 95, "name": "Send empty strings to webservices", "short_name": "ses", "uid": "7f11ab99-79a8-417c-93ce-022159e4bd8b", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "sendemptystrings", "parameter": true, "order": 2, "description": ""}}, {"pk": 301, "model": "workflows.abstractinput", "fields": {"widget": 96, "name": "Send empty strings to webservices", "short_name": "ses", "uid": "306aa32b-0c75-41e7-8a12-1dbad868124c", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "sendemptystrings", "parameter": true, "order": 2, "description": ""}}, {"pk": 303, "model": "workflows.abstractinput", "fields": {"widget": 97, "name": "Send empty strings to webservices", "short_name": "ses", "uid": "21155ff6-e3dc-4b73-99be-7070bc16a7ac", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "sendemptystrings", "parameter": true, "order": 2, "description": ""}}, {"pk": 307, "model": "workflows.abstractinput", "fields": {"widget": 98, "name": "Send empty strings to webservices", "short_name": "ses", "uid": "00fdd694-785f-4e96-a616-5feea30eec49", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "sendemptystrings", "parameter": true, "order": 2, "description": ""}}, {"pk": 312, "model": "workflows.abstractinput", "fields": {"widget": 99, "name": "Send empty strings to webservices", "short_name": "ses", "uid": "48127408-7f94-47bc-93d7-723787cccbe9", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "sendemptystrings", "parameter": true, "order": 2, "description": ""}}, {"pk": 315, "model": "workflows.abstractinput", "fields": {"widget": 100, "name": "Send empty strings to webservices", "short_name": "ses", "uid": "9d4e54cc-013a-4997-8804-bc6329901226", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "sendemptystrings", "parameter": true, "order": 2, "description": ""}}, {"pk": 318, "model": "workflows.abstractinput", "fields": {"widget": 101, "name": "Send empty strings to webservices", "short_name": "ses", "uid": "80e54d5f-d86f-4681-8bad-8b37cc1ec2c3", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "sendemptystrings", "parameter": true, "order": 2, "description": ""}}, {"pk": 322, "model": "workflows.abstractinput", "fields": {"widget": 102, "name": "Send empty strings to webservices", "short_name": "ses", "uid": "8b63a66a-2a37-41d0-8c55-8b92f98fc79f", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "sendemptystrings", "parameter": true, "order": 2, "description": ""}}, {"pk": 326, "model": "workflows.abstractinput", "fields": {"widget": 103, "name": "Send empty strings to webservices", "short_name": "ses", "uid": "ee7f6b67-f6ef-4801-afdc-e7aab6656dd7", "default": "", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "sendemptystrings", "parameter": true, "order": 2, "description": ""}}, {"pk": 328, "model": "workflows.abstractinput", "fields": {"widget": 104, "name": "Send empty strings to webservices", "short_name": "ses", "uid": "69e8a087-14b7-4539-bea2-07450fb40cdd", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "sendemptystrings", "parameter": true, "order": 2, "description": ""}}, {"pk": 332, "model": "workflows.abstractinput", "fields": {"widget": 105, "name": "Send empty strings to webservices", "short_name": "ses", "uid": "7ac0ea58-70b3-4e75-a146-2abcd9ff81a0", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "sendemptystrings", "parameter": true, "order": 2, "description": ""}}, {"pk": 336, "model": "workflows.abstractinput", "fields": {"widget": 106, "name": "Send empty strings to webservices", "short_name": "ses", "uid": "e91780de-4643-4e7d-86a7-6fe3f4d81324", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "sendemptystrings", "parameter": true, "order": 2, "description": ""}}, {"pk": 338, "model": "workflows.abstractinput", "fields": {"widget": 107, "name": "Class Index", "short_name": "ci", "uid": "ef5fbfe5-72dc-4e3d-9d88-239caeeed56e", "default": "-1", "required": false, "multi": false, "parameter_type": "text", "variable": "classIndex", "parameter": true, "order": 2, "description": "Class index. 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In Single linkage clustering, the distance between two clusters is defined as the distance between the closest elements of the two clusters. Average linkage clustering computes the average distance between elements of the two clusters, and Complete linkage defines the distance between two clusters as the distance between their most distant elements."}}, {"pk": 376, "model": "workflows.abstractinput", "fields": {"widget": 125, "name": "Orange Data Table", "short_name": "odt", "uid": "3de89884-15aa-40dd-a514-cb7e7d5298c5", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "data", "parameter": false, "order": 2, "description": ""}}, {"pk": 380, "model": "workflows.abstractinput", "fields": {"widget": 127, "name": "Orange Data Table", "short_name": "odt", "uid": "aa5d2630-534f-4662-8da5-342b2e87995b", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "data", "parameter": false, "order": 2, "description": ""}}, {"pk": 384, "model": "workflows.abstractinput", "fields": {"widget": 129, "name": "Learner", "short_name": "lrn", "uid": "a7f392fe-55f7-48df-9afb-1d0044562a2a", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "learner", "parameter": false, "order": 2, "description": ""}}, {"pk": 388, "model": "workflows.abstractinput", "fields": {"widget": 132, "name": "Cutoff", "short_name": "ctf", "uid": "c6fa462e-df86-424e-8803-3ded38ee6f73", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "cutoff", "parameter": true, "order": 2, "description": "We can also add the keyword argument cutoff (e.g. confusionMatrices(results, cutoff=0.3); if we do, confusionMatrices will disregard the classifiers' class predictions and observe the predicted probabilities, and consider the prediction \"positive\" if the predicted probability of the positive class is higher than the cutoff."}}, {"pk": 390, "model": "workflows.abstractinput", "fields": {"widget": 133, "name": "Report Standard Error", "short_name": "rse", "uid": "34afe990-c3e7-40ac-93c9-15283b3e12fc", "default": "", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "reportSE", "parameter": true, "order": 2, "description": ""}}, {"pk": 392, "model": "workflows.abstractinput", "fields": {"widget": 134, "name": "Scores", "short_name": "sco", "uid": "2e60fc2e-3470-46d3-a64f-ab1e7c75487b", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "scores", "parameter": false, "order": 2, "description": ""}}, {"pk": 395, "model": "workflows.abstractinput", "fields": {"widget": 135, "name": "Scores", "short_name": "sco", "uid": "a19e140e-4aab-4491-9536-992152a3d56f", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "scores", "parameter": false, "order": 2, "description": ""}}, {"pk": 400, "model": "workflows.abstractinput", "fields": {"widget": 137, "name": "Learners", "short_name": "lrn", "uid": "499f4007-55c3-431c-93ca-5f493a9e592c", "default": "", "required": false, "multi": true, "parameter_type": null, "variable": "learners", "parameter": false, "order": 2, "description": ""}}, {"pk": 405, "model": "workflows.abstractinput", "fields": {"widget": 140, "name": "k", "short_name": "k", "uid": "3ef628d4-03af-4d46-b90b-6c4475054d31", "default": "20", "required": false, "multi": false, "parameter_type": "text", "variable": "k", "parameter": true, "order": 2, "description": ""}}, {"pk": 408, "model": "workflows.abstractinput", "fields": {"widget": 143, "name": "alpha", "short_name": "alp", "uid": "26e4f697-0231-4cf8-8cbd-2cb325441ba7", "default": "2.0", "required": false, "multi": false, "parameter_type": "text", "variable": "alpha", "parameter": true, "order": 2, "description": ""}}, {"pk": 414, "model": "workflows.abstractinput", "fields": {"widget": 146, "name": "Distance Metrics", "short_name": "dm", "uid": "df5d4372-6365-4285-9c8b-261bb620ca39", "default": "0", "required": false, "multi": false, "parameter_type": "select", "variable": "distanceMetrics", "parameter": true, "order": 2, "description": "The available Distance Metrics definitions are Euclidean, Manhattan, Hammming and Relief. Besides, of course, different formal definitions, the measures also differ in how correctly they treat unknown values. Manhattan and Hamming distance do not excel in this respect; Relief distance is similar to Manhattan, but with a more correct treatment for discrete attributes."}}, {"pk": 415, "model": "workflows.abstractinput", "fields": {"widget": 147, "name": "Report Standard Error", "short_name": "rse", "uid": "49a8722a-74b9-4cd6-a9bf-aec25ff05120", "default": "", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "reportSE", "parameter": true, "order": 2, "description": ""}}, {"pk": 417, "model": "workflows.abstractinput", "fields": {"widget": 148, "name": "Split factor", "short_name": "p", "uid": "6a637f14-7ba4-4c33-90e0-6cc260587260", "default": "0.5", "required": false, "multi": false, "parameter_type": "text", "variable": "p", "parameter": true, "order": 2, "description": "A number between 0 and 1 that determines the sizes of the two datasets"}}, {"pk": 420, "model": "workflows.abstractinput", "fields": {"widget": 149, "name": "Measures for attributes", "short_name": "mat", "uid": "cc42fca8-68a7-4874-b369-49e4bb4fa85f", "default": "0", "required": false, "multi": false, "parameter_type": "select", "variable": "classInteractions", "parameter": true, "order": 2, "description": "The two kinds of attributes (discrete and continuous) have different measures of distance."}}, {"pk": 423, "model": "workflows.abstractinput", "fields": {"widget": 150, "name": "List of precisions", "short_name": "pre", "uid": "91b5674a-88e7-4954-9117-46c1fbeb2d4c", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "precision", "parameter": false, "order": 2, "description": ""}}, {"pk": 425, "model": "workflows.abstractinput", "fields": {"widget": 153, "name": "Report Standard Error", "short_name": "rse", "uid": "322d1975-8cff-423c-b73a-e7f5a1488e2e", "default": "", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "reportSE", "parameter": true, "order": 2, "description": ""}}, {"pk": 429, "model": "workflows.abstractinput", "fields": {"widget": 156, "name": "Orange Data Table", "short_name": "odt", "uid": "2b2037f4-b240-4b26-81e5-8ca01a215193", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "dataset", "parameter": false, "order": 2, "description": ""}}, {"pk": 435, "model": "workflows.abstractinput", "fields": {"widget": 158, "name": "Method", "short_name": "met", "uid": "538f7e3a-8650-4c33-ad49-d00221d86145", "default": "0", "required": false, "multi": false, "parameter_type": "select", "variable": "method", "parameter": true, "order": 2, "description": ""}}, {"pk": 438, "model": "workflows.abstractinput", "fields": {"widget": 160, "name": "k", "short_name": "k", "uid": "d6f4067c-39c3-4ea5-80f8-77759db7b2dc", "default": "20", "required": false, "multi": false, "parameter_type": "text", "variable": "k", "parameter": true, "order": 2, "description": ""}}, {"pk": 443, "model": "workflows.abstractinput", "fields": {"widget": 164, "name": "Report Standard Error", "short_name": "rse", "uid": "3dfeb6f5-fe7a-461a-b965-de7daa0b61eb", "default": "", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "reportSE", "parameter": true, "order": 2, "description": ""}}, {"pk": 447, "model": "workflows.abstractinput", "fields": {"widget": 166, "name": "Discretizators", "short_name": "dis", "uid": "6facdb69-d2e9-4625-bfaf-0b498adba715", "default": "0", "required": false, "multi": false, "parameter_type": "select", "variable": "discretizer_id", "parameter": true, "order": 2, "description": "Example-based automatic discretization is in essence similar to learning: given a set of examples, discretization method proposes a list of suitable intervals to cut the attribute's values into. For this reason, Orange structures for discretization resemble its structures for learning. Objects derived from orange.Discretization play a role of \"learner\" that, upon observing the examples, construct an orange.Discretizer whose role is to convert continuous values into discrete according to the rule found by Discretization."}}, {"pk": 450, "model": "workflows.abstractinput", "fields": {"widget": 170, "name": "Detected Noise", "short_name": "dni", "uid": "345a8672-386a-4bc5-b7ff-d7a3a9ee4b0c", "default": "", "required": true, "multi": true, "parameter_type": null, "variable": "detected_noise", "parameter": false, "order": 2, "description": ""}}, {"pk": 454, "model": "workflows.abstractinput", "fields": {"widget": 171, "name": "Detected Instances", "short_name": "dti", "uid": "da95100a-ec91-46d7-9244-b642aab9bf0d", "default": "", "required": false, "multi": true, "parameter_type": null, "variable": "detected_inds", "parameter": false, "order": 2, "description": ""}}, {"pk": 457, "model": "workflows.abstractinput", "fields": {"widget": 173, "name": "Algorithm Performance", "short_name": "alp", "uid": "9bd36b53-7c9a-4ce7-a591-acecfe1bdc14", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "performance", "parameter": false, "order": 2, "description": ""}}, {"pk": 460, "model": "workflows.abstractinput", "fields": {"widget": 175, "name": "F-measure Beta-parameter", "short_name": "btp", "uid": "c584ebf0-a9b4-4877-b503-2abef8c7dd72", "default": "1", "required": true, "multi": false, "parameter_type": "text", "variable": "beta", "parameter": true, "order": 2, "description": ""}}, {"pk": 464, "model": "workflows.abstractinput", "fields": {"widget": 177, "name": "discretization intervals", "short_name": "itr", "uid": "e20c7a7c-d2f5-4ab6-9ef1-b3d244140d88", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "discr_intervals", "parameter": false, "order": 2, "description": "dictionary of intervals for discretization"}}, {"pk": 467, "model": "workflows.abstractinput", "fields": {"widget": 178, "name": "password", "short_name": "pwd", "uid": "8ead911a-3d1b-4e50-b56a-64873b85d3cf", "default": "", "required": false, "multi": false, "parameter_type": "password", "variable": "password", "parameter": true, "order": 2, "description": ""}}, {"pk": 471, "model": "workflows.abstractinput", "fields": {"widget": 179, "name": "format", "short_name": "fmt", "uid": "6990c6fd-615e-41b7-912c-ad31dd169065", "default": "arff", "required": true, "multi": false, "parameter_type": "select", "variable": "output_format", "parameter": true, "order": 2, "description": "output format"}}, {"pk": 475, "model": "workflows.abstractinput", "fields": {"widget": 180, "name": "Table connection from names", "short_name": "tbc", "uid": "be3718eb-062e-48f2-af2a-8c31e66524fe", "default": "false", "required": true, "multi": false, "parameter_type": "checkbox", "variable": "find_connections", "parameter": true, "order": 2, "description": "Tries to detect connections between tables solely by looking at the attribute names."}}, {"pk": 476, "model": "workflows.abstractinput", "fields": {"widget": 181, "name": "format", "short_name": "fmt", "uid": "5765110e-ead7-463b-8af4-c710dd0e56f4", "default": "arff", "required": true, "multi": false, "parameter_type": "select", "variable": "output_format", "parameter": true, "order": 2, "description": "output format"}}, {"pk": 482, "model": "workflows.abstractinput", "fields": {"widget": 182, "name": "discretization intervals", "short_name": "itr", "uid": "ebda708e-1ef8-4326-8788-1c98611c7817", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "discr_intervals", "parameter": false, "order": 2, "description": "dictionary of intervals for discretization"}}, {"pk": 483, "model": "workflows.abstractinput", "fields": {"widget": 183, "name": "format", "short_name": "fmt", "uid": "1b119724-6e2f-48f6-9cea-7712da9bd57f", "default": "arff", "required": true, "multi": false, "parameter_type": "select", "variable": 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"uid": "cfdfd105-8eb0-4a7a-bf06-2df3e25f4880", "default": "auto", "required": false, "multi": false, "parameter_type": "select", "variable": "algIn", "parameter": true, "order": 2, "description": ""}}, {"pk": 507, "model": "workflows.abstractinput", "fields": {"widget": 199, "name": "C", "short_name": "par", "uid": "78a44bbf-4da4-46e1-9be2-e3335b04c74b", "default": "1.0", "required": false, "multi": false, "parameter_type": "text", "variable": "cIn", "parameter": true, "order": 2, "description": ""}}, {"pk": 512, "model": "workflows.abstractinput", "fields": {"widget": 202, "name": "Loss parameter(loss)", "short_name": "par", "uid": "4511ba8c-015c-4e26-8ca4-164c74afde18", "default": "l2", "required": false, "multi": false, "parameter_type": "select", "variable": "lossIn", "parameter": true, "order": 2, "description": ""}}, {"pk": 516, "model": "workflows.abstractinput", "fields": {"widget": 205, "name": "ScikitDataset", "short_name": "dts", "uid": "2cf65003-ff21-4c06-8783-0473fe66195d", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "data", "parameter": false, "order": 2, "description": ""}}, {"pk": 520, "model": "workflows.abstractinput", "fields": {"widget": 208, "name": "Words", "short_name": "wrd", "uid": "69b06741-8055-4dad-b677-3940d3434bc2", "default": "", "required": false, "multi": false, "parameter_type": "textarea", "variable": "words", "parameter": true, "order": 2, "description": "One word or phrase per line"}}, {"pk": 524, "model": "workflows.abstractinput", "fields": {"widget": 210, "name": "Geocode", "short_name": "geo", "uid": "80d1e542-7f7c-4a8e-b683-764d0a754b03", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "geocode", "parameter": true, "order": 2, "description": ""}}, {"pk": 530, "model": "workflows.abstractinput", "fields": {"widget": 212, "name": "Language", "short_name": "lan", "uid": "9befb8ed-7644-4f41-8887-1c6f74bdeba7", "default": "en", "required": false, "multi": false, "parameter_type": "text", "variable": "lang", "parameter": true, "order": 2, "description": ""}}, {"pk": 532, "model": "workflows.abstractinput", "fields": {"widget": 213, "name": "Neutral zone", "short_name": "nz", "uid": "607375c0-f4e3-43b8-9f99-2830ac7e5c83", "default": "0.1", "required": false, "multi": false, "parameter_type": "text", "variable": "zone", "parameter": true, "order": 2, "description": "A value between 0 and 1"}}, {"pk": 542, "model": "workflows.abstractinput", "fields": {"widget": 221, "name": "Size", "short_name": "siz", "uid": "fb2215c6-04e6-4c0b-97e5-f380c4b2f6e8", "default": "500", "required": false, "multi": false, "parameter_type": "text", "variable": "size", "parameter": true, "order": 2, "description": "Window size"}}, {"pk": 547, "model": "workflows.abstractinput", "fields": {"widget": 223, "name": "Batch size", "short_name": "b", "uid": "c36187d3-5df0-4f06-85b0-d01ea921f7b3", "default": "100", "required": false, "multi": false, "parameter_type": "text", "variable": "b_size", "parameter": true, "order": 2, "description": "Number of tweets for hand-labeling chosen with the \"Closest to the neutral zone\""}}, {"pk": 565, "model": "workflows.abstractinput", "fields": {"widget": 241, "name": "Vocabulary", "short_name": "voc", "uid": "c22ffaaf-ea30-4298-a83f-226276cb9097", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "vocabulary", "parameter": false, "order": 2, "description": "Bio3graph vocabulary structure."}}, {"pk": 567, "model": "workflows.abstractinput", "fields": {"widget": 242, "name": "Relations", "short_name": "rls", "uid": "93cb1318-763a-435d-9304-a33e3bf20299", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "relations", "parameter": false, "order": 2, "description": "List of relations"}}, {"pk": 569, "model": "workflows.abstractinput", "fields": {"widget": 243, "name": "Vocabulary", "short_name": "voc", "uid": "9f71a834-c06d-410f-a9a3-cbd9db28a0bb", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "vocabulary", "parameter": false, "order": 2, "description": "Bio3graph vocabulary structure."}}, {"pk": 574, "model": "workflows.abstractinput", "fields": {"widget": 245, "name": "Activation", "short_name": "act", "uid": "913b8b8b-9d99-4f24-ae48-db25f3490187", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "activation", "parameter": false, "order": 2, "description": "CSV file with activations."}}, {"pk": 580, "model": "workflows.abstractinput", "fields": {"widget": 247, "name": "New network", "short_name": "nnw", "uid": "0c36aec5-7df4-4406-8d3c-d2c10cd876ed", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "new_network", "parameter": false, "order": 2, "description": "New network as a NetworkX data structure."}}, {"pk": 586, "model": "workflows.abstractinput", "fields": {"widget": 251, "name": "New network", "short_name": "nwx", "uid": "2359acc6-7680-4a8f-aa75-34f1a216dd4d", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "new_network", "parameter": false, "order": 2, "description": "New network as NetworkX data structure"}}, {"pk": 590, "model": "workflows.abstractinput", "fields": {"widget": 255, "name": "query", "short_name": "q", "uid": "67b45d4f-32a5-415f-ad53-8a2caf1cd3d1", "default": "", "required": true, "multi": false, "parameter_type": "textarea", "variable": "query", "parameter": true, "order": 2, "description": "PubMed query"}}, {"pk": 593, "model": "workflows.abstractinput", "fields": {"widget": 256, "name": "Relations", "short_name": "rls", "uid": "b42536ae-979b-441f-ad6d-e7a76e22db5e", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "relations", "parameter": false, "order": 2, "description": "List of relations"}}, {"pk": 595, "model": "workflows.abstractinput", "fields": {"widget": 258, "name": "Threshold", "short_name": "thd", "uid": "b44f486b-4459-435d-b89a-20809e1fdf9c", "default": "10", "required": true, "multi": false, "parameter_type": "select", "variable": "treshold", "parameter": true, "order": 2, "description": ""}}, {"pk": 597, "model": "workflows.abstractinput", "fields": {"widget": 259, "name": "Learner", "short_name": "lrn", "uid": "a111962a-9cff-418a-8ad9-037569cfd2c3", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "learner", "parameter": false, "order": 2, "description": ""}}, {"pk": 603, "model": "workflows.abstractinput", "fields": {"widget": 261, "name": "Dataset", "short_name": "ds", "uid": "fd433309-d6b5-4fea-b99c-e55152a87e7a", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "data", "parameter": false, "order": 2, "description": ""}}, {"pk": 604, "model": "workflows.abstractinput", "fields": {"widget": 262, "name": "Noisy Instances", "short_name": "nsi", "uid": "609eae39-00b0-4713-ba0e-55f54e7d642e", "default": "", "required": false, "multi": true, "parameter_type": null, "variable": "noise", "parameter": false, "order": 2, "description": ""}}, {"pk": 609, "model": "workflows.abstractinput", "fields": {"widget": 265, "name": "Chart title", "short_name": "ttl", "uid": "ee7d6063-1bd7-4cd5-98c3-605a1c4a10f3", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "title", "parameter": true, "order": 2, "description": ""}}, {"pk": 610, "model": "workflows.abstractinput", "fields": {"widget": 266, "name": "Chart title", "short_name": "ttl", "uid": "1bfa000e-e224-424b-b602-8191dc705f8a", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "title", "parameter": true, "order": 2, "description": ""}}, {"pk": 615, "model": "workflows.abstractinput", "fields": {"widget": 269, "name": "Chart title", "short_name": "ttl", "uid": "e8b01dca-c94e-473e-b4ce-3f45a2ce1d10", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "title", "parameter": true, "order": 2, "description": ""}}, {"pk": 616, "model": "workflows.abstractinput", "fields": {"widget": 270, "name": "Chart title", "short_name": "ttl", "uid": "040a9932-a5d5-465c-889d-ddc45bc68c5b", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "title", "parameter": true, "order": 2, "description": ""}}, {"pk": 618, "model": "workflows.abstractinput", "fields": {"widget": 271, "name": "Chart title", "short_name": "ttl", "uid": "76d078ee-c5e7-4a4c-9347-a7884305cbc8", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "title", "parameter": true, "order": 2, "description": ""}}, {"pk": 622, "model": "workflows.abstractinput", "fields": {"widget": 273, "name": "Prediction Type", "short_name": "typ", "uid": "783b6e0b-ba48-4346-a8f2-94c7a719d85f", "default": "-score", "required": true, "multi": false, "parameter_type": "select", "variable": "subtype", "parameter": true, "order": 2, "description": "Prediction scores or ranks"}}, {"pk": 623, "model": "workflows.abstractinput", "fields": {"widget": 274, "name": "Chart title", "short_name": "ttl", "uid": "6827d783-52bf-466c-875d-9163cc23e3be", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "title", "parameter": true, "order": 2, "description": ""}}, {"pk": 625, "model": "workflows.abstractinput", "fields": {"widget": 275, "name": "Chart title", "short_name": "ttl", "uid": "72ab4bab-aeac-4530-b75e-8f86ca9e12c1", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "title", "parameter": true, "order": 2, "description": ""}}, {"pk": 629, "model": "workflows.abstractinput", "fields": {"widget": 276, "name": "Name", "short_name": "nam", "uid": "76171f1b-e2f9-4bf5-a825-f8bec8d047d6", "default": "", "required": true, "multi": false, "parameter_type": "text", "variable": "name", "parameter": true, "order": 2, "description": ""}}, {"pk": 631, "model": "workflows.abstractinput", "fields": {"widget": 277, "name": "Server link", "short_name": "url", "uid": "585e80d1-e5fb-49c9-92a7-7af16d4070f6", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "unitylink", "parameter": false, "order": 2, "description": "Link to the Unity3D server"}}, {"pk": 633, "model": "workflows.abstractinput", "fields": {"widget": 278, "name": "Service url", "short_name": "url", "uid": "2a896528-9e04-41e3-ba36-1d005c965db9", "default": "http://vihar.ijs.si:8001/MUSE_services/jsonwsp/description", "required": true, "multi": false, "parameter_type": "text", "variable": "url", "parameter": true, "order": 2, "description": "URL of the MUSE service"}}, {"pk": 635, "model": "workflows.abstractinput", "fields": {"widget": 280, "name": "Service url", "short_name": "url", "uid": "814c5076-50b6-40de-a0d8-1b81aceb4f9f", "default": "http://vihar.ijs.si:8001/MUSE_services/jsonwsp/description", "required": true, "multi": false, "parameter_type": "text", "variable": "url", "parameter": true, "order": 2, "description": "URL of the MUSE service"}}, {"pk": 638, "model": "workflows.abstractinput", "fields": {"widget": 281, "name": "Service url", "short_name": "url", "uid": "cbc553ec-1650-459d-bcdd-cf41636b6a56", "default": "http://vihar.ijs.si:8001/MUSE_services/jsonwsp/description", "required": true, "multi": false, "parameter_type": "text", "variable": "url", "parameter": true, "order": 2, "description": "URL of the MUSE service"}}, {"pk": 642, "model": "workflows.abstractinput", "fields": {"widget": 284, "name": "Service url", "short_name": "url", "uid": "c47d762d-b3a7-46b8-9bfd-7579bf0dcc56", "default": "http://vihar.ijs.si:8001/MUSE_services/jsonwsp/description", "required": true, "multi": false, "parameter_type": "text", "variable": "url", "parameter": true, "order": 2, "description": "URL of the MUSE service"}}, {"pk": 644, "model": "workflows.abstractinput", "fields": {"widget": 285, "name": "File extension", "short_name": "typ", "uid": "a948226a-881f-4b8d-9739-6c99a57a8837", "default": ".xml", "required": true, "multi": false, "parameter_type": "text", "variable": "fending", "parameter": true, "order": 2, "description": "Extension of the static file"}}, {"pk": 646, "model": "workflows.abstractinput", "fields": {"widget": 286, "name": "Service url", "short_name": "url", "uid": "a9e1d01c-af14-4826-bac3-1f8fbd37b595", "default": "http://vihar.ijs.si:8001/MUSE_services/jsonwsp/description", "required": true, "multi": false, "parameter_type": "text", "variable": "url", "parameter": true, "order": 2, "description": "URL of the MUSE service"}}, {"pk": 647, "model": "workflows.abstractinput", "fields": {"widget": 287, "name": "Service url", "short_name": "url", "uid": "fd076e47-1432-4678-8353-aeb4ec286ecf", "default": "http://vihar.ijs.si:8001/MUSE_services/jsonwsp/description", "required": true, "multi": false, "parameter_type": "text", "variable": "url", "parameter": true, "order": 2, "description": "URL of the MUSE service"}}, {"pk": 652, "model": "workflows.abstractinput", "fields": {"widget": 290, "name": "Service url", "short_name": "url", "uid": "2b6b393c-97c7-4827-94a5-042944382939", "default": "http://vihar.ijs.si:8001/MUSE_services/jsonwsp/description", "required": true, "multi": false, "parameter_type": "text", "variable": "url", "parameter": true, "order": 2, "description": "URL of the MUSE service"}}, {"pk": 655, "model": "workflows.abstractinput", "fields": {"widget": 291, "name": "Unity3D app link", "short_name": "lnk", "uid": "adfdaa7d-4e2e-4d98-aaa0-a33df67c381e", "default": "https://ive.scm.tees.ac.uk/muse/tuk-text/Tuk-Text-Workflow-Web.html", "required": true, "multi": false, "parameter_type": "text", "variable": "unityLink", "parameter": true, "order": 2, "description": "A link to the Tuk Unity3D web app"}}, {"pk": 657, "model": "workflows.abstractinput", "fields": {"widget": 292, "name": "Service url", "short_name": "url", "uid": "63156d94-df63-495e-96dd-17bb7cf78b35", "default": "http://vihar.ijs.si:8001/MUSE_services/jsonwsp/description", "required": true, "multi": false, "parameter_type": "text", "variable": "url", "parameter": true, "order": 2, "description": "URL of the MUSE service"}}, {"pk": 661, "model": "workflows.abstractinput", "fields": {"widget": 296, "name": "Dataset", "short_name": "dst", "uid": "5b9aba72-163c-4862-af26-173b3b2cda7a", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "dataset", "parameter": false, "order": 2, "description": ""}}, {"pk": 662, "model": "workflows.abstractinput", "fields": {"widget": 297, "name": "Convergence", "short_name": "con", "uid": "104f5edc-6029-4ae8-8a83-29557fa901fd", "default": "1e-8", "required": true, "multi": false, "parameter_type": "text", "variable": "alpha", "parameter": true, "order": 2, "description": "The value defines the convergence of the logistic regression."}}, {"pk": 669, "model": "workflows.abstractinput", "fields": {"widget": 298, "name": "URL range", "short_name": "rng", "uid": "992a24e0-0365-46ef-8dd2-37fa19563bd5", "default": "", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "range", "parameter": true, "order": 2, "description": "The URL range parameter is used with URLs that point to file chunks, named as xaaaa to xzzzz. This naming is provided by the unix split command. The first and last URL should be defined in the URLs text box. Intermediate URLs will be automatically generated."}}, {"pk": 677, "model": "workflows.abstractinput", "fields": {"widget": 299, "name": "Dataset", "short_name": "dst", "uid": "ae2aaa2e-93d8-427c-9631-d053581ad888", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "dataset", "parameter": false, "order": 2, "description": ""}}, {"pk": 679, "model": "workflows.abstractinput", "fields": {"widget": 300, "name": "Additional parameters", "short_name": "adp", "uid": "a194ac52-5e13-46c2-be48-a9b531da4d33", "default": "", "required": true, "multi": false, "parameter_type": "checkbox", "variable": "add_params", "parameter": true, "order": 2, "description": ""}}, {"pk": 690, "model": "workflows.abstractinput", "fields": {"widget": 303, "name": "The weighting factor", "short_name": "nu", "uid": "e9b6cbcd-fc02-478b-a993-3b42ee730857", "default": "0.1", "required": true, "multi": false, "parameter_type": "text", "variable": "nu", "parameter": true, "order": 2, "description": ""}}, {"pk": 691, "model": "workflows.abstractinput", "fields": {"widget": 304, "name": "Dataset", "short_name": "dst", "uid": "08f26e43-9ceb-4081-b00c-265c567096b2", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "dataset", "parameter": false, "order": 2, "description": ""}}, {"pk": 695, "model": "workflows.abstractinput", "fields": {"widget": 305, "name": "Dataset", "short_name": "dst", "uid": "f3f54b2d-ba4b-440d-8600-c3630deec970", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "dataset", "parameter": false, "order": 2, "description": ""}}, {"pk": 696, "model": "workflows.abstractinput", "fields": {"widget": 306, "name": "Dataset", "short_name": "dst", "uid": "42897594-631a-415e-b71a-d92668c9e1cb", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "dataset", "parameter": false, "order": 2, "description": ""}}, {"pk": 712, "model": "workflows.abstractinput", "fields": {"widget": 309, "name": "Dataset", "short_name": "dst", "uid": "1a7bab82-8d0f-4372-93ce-6abe6cba1779", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "dataset", "parameter": false, "order": 2, "description": ""}}, {"pk": 715, "model": "workflows.abstractinput", "fields": {"widget": 310, "name": "Number of clusters", "short_name": "cls", "uid": "48f3025a-1bcc-41a1-985f-f2b3ae9633e7", "default": "3", "required": true, "multi": false, "parameter_type": "text", "variable": "clusters", "parameter": true, "order": 2, "description": ""}}, {"pk": 718, "model": "workflows.abstractinput", "fields": {"widget": 311, "name": "Fitting dataset", "short_name": "dst", "uid": "104d08df-fe2a-4c11-8432-e33389017f9e", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "fitting_dataset", "parameter": false, "order": 2, "description": "Define a dataset that will be fitted to training dataset."}}, {"pk": 722, "model": "workflows.abstractinput", "fields": {"widget": 312, "name": "Dataset", "short_name": "dst", "uid": "59fcf118-8d2d-4789-b91a-f31b2d62e141", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "dataset", "parameter": false, "order": 2, "description": ""}}, {"pk": 728, "model": "workflows.abstractinput", "fields": {"widget": 314, "name": "Naive Bayes - m estimate", "short_name": "m", "uid": "a247302f-c63d-4473-9869-c93e330b0c48", "default": "1", "required": true, "multi": false, "parameter_type": "text", "variable": "m", "parameter": true, "order": 2, "description": "m estimate"}}, {"pk": 731, "model": "workflows.abstractinput", "fields": {"widget": 315, "name": "Dataset", "short_name": "dst", "uid": "ce059641-3abd-49e1-9c55-d3476e0db0ee", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "dataset", "parameter": false, "order": 2, "description": ""}}, {"pk": 740, "model": "workflows.abstractinput", "fields": {"widget": 321, "name": "Offset", "short_name": "off", "uid": "6fef5306-e341-4794-a1c0-57c6a74c15e0", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "offset", "parameter": true, "order": 2, "description": "Input must be a number. This input influences how many inputs we should skip in the beginning."}}, {"pk": 54, "model": "workflows.abstractinput", "fields": {"widget": 36, "name": "Fold change: Calculation method", "short_name": "m", "uid": "f3c2883f-e4a6-4c2b-90d8-07a73af84708", "default": "1", "required": true, "multi": false, "parameter_type": "select", "variable": "cm", "parameter": true, "order": 3, "description": "Specifies fold change calculation method."}}, {"pk": 67, "model": "workflows.abstractinput", "fields": {"widget": 40, "name": "GSEA test weight", "short_name": "wgs", "uid": "ae23e1d3-dd0b-492b-9786-107738f2892e", "default": "1.0", "required": false, "multi": false, "parameter_type": "text", "variable": "weightGSEA", "parameter": true, "order": 3, "description": "GSEA test weight"}}, {"pk": 93, "model": "workflows.abstractinput", "fields": {"widget": 43, "name": "GSEA test weight", "short_name": "wgs", "uid": "e6ecb0af-f861-4a9f-8db6-eb52a7514b0e", "default": "1.0", "required": false, "multi": false, "parameter_type": "text", "variable": "weightGSEA", "parameter": true, "order": 3, "description": "GSEA test weight"}}, {"pk": 98, "model": "workflows.abstractinput", "fields": {"widget": 44, "name": "Upper bound", "short_name": "ub", "uid": "89f39076-f11d-4d50-a91c-e4db60781b2f", "default": "0.3", "required": false, "multi": false, "parameter_type": "text", "variable": "upper", "parameter": true, "order": 3, "description": "upper bound for cutoff"}}, {"pk": 101, "model": "workflows.abstractinput", "fields": {"widget": 45, "name": "Reference examples (0 = all)", "short_name": "m", "uid": "11fd645a-cf41-4774-98aa-759478c94588", "default": "0", "required": false, "multi": false, "parameter_type": "text", "variable": "m", "parameter": true, "order": 3, "description": ""}}, {"pk": 115, "model": "workflows.abstractinput", "fields": {"widget": 55, "name": "End nodes", "short_name": "end", "uid": "9a0dc048-ae26-4bb8-ba90-76521b4843b3", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "endNodes", "parameter": false, "order": 3, "description": "End nodes"}}, {"pk": 132, "model": "workflows.abstractinput", "fields": {"widget": 57, "name": "GSEA test weight", "short_name": "wgs", "uid": "c1b246b4-7b00-4447-9e05-166fb84a7854", "default": "1.0", "required": false, "multi": false, "parameter_type": "text", "variable": "weightGSEA", "parameter": true, "order": 3, "description": "GSEA test weight"}}, {"pk": 142, "model": "workflows.abstractinput", "fields": {"widget": 59, "name": "Single component", "short_name": "scm", "uid": "980f228d-94b5-4523-9a65-2d4d3d6a6521", "default": "", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "singleComponent", "parameter": true, "order": 3, "description": "Single component"}}, {"pk": 147, "model": "workflows.abstractinput", "fields": {"widget": 61, "name": "Single component", "short_name": "scm", "uid": "adbdd779-8bad-433b-835e-c14ba567d96f", "default": "", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "singleComponent", "parameter": true, "order": 3, "description": "Single component"}}, {"pk": 152, "model": "workflows.abstractinput", "fields": {"widget": 62, "name": "Database", "short_name": "dbs", "uid": "cbdafcda-e0a8-4e8d-9684-f65023ec5b5b", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "dbname", "parameter": false, "order": 3, "description": "Name of the database to use"}}, {"pk": 163, "model": "workflows.abstractinput", "fields": {"widget": 70, "name": "Minimal TP Rate", "short_name": "tpr", "uid": "84eaef35-dab6-4b5b-92fd-b75c2d9f139c", "default": "0.8", "required": false, "multi": false, "parameter_type": "text", "variable": "minTPrate", "parameter": true, "order": 3, "description": "Minimal True Positive Rate"}}, {"pk": 166, "model": "workflows.abstractinput", "fields": {"widget": 71, "name": "Language", "short_name": "lan", "uid": "ceb04ed2-a444-499e-b24f-db6cb28f7e2c", "default": "en", "required": true, "multi": false, "parameter_type": "select", "variable": "lang", "parameter": true, "order": 3, "description": "Language"}}, {"pk": 170, "model": "workflows.abstractinput", "fields": {"widget": 72, "name": "XML output", "short_name": "xml", "uid": "a47a5353-fee0-414b-8393-db0af3bc93b9", "default": "false", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "xml", "parameter": true, "order": 3, "description": "Output results as XML"}}, {"pk": 182, "model": "workflows.abstractinput", "fields": {"widget": 73, "name": "Annotations", "short_name": "ann", "uid": "d8ee7029-f645-403c-94da-c5ea6f4f901a", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "annotations", "parameter": false, "order": 3, "description": "Totrtale annotations"}}, {"pk": 187, "model": "workflows.abstractinput", "fields": {"widget": 74, "name": "Language", "short_name": "lan", "uid": "a509c622-a31e-4b51-8d11-7793ea923b71", 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"default": "", "required": true, "multi": false, "parameter_type": null, "variable": "data", "parameter": false, "order": 3, "description": ""}}, {"pk": 630, "model": "workflows.abstractinput", "fields": {"widget": 276, "name": "Predicted dataset", "short_name": "odp", "uid": "7a4682dc-a479-488b-a5c9-8c8576af48ec", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "predicted", "parameter": false, "order": 3, "description": ""}}, {"pk": 664, "model": "workflows.abstractinput", "fields": {"widget": 297, "name": "Max. number of iterations", "short_name": "itr", "uid": "73fbdb1a-8889-46d9-8eed-907156de7956", "default": "10", "required": true, "multi": false, "parameter_type": "text", "variable": "itr", "parameter": true, "order": 3, "description": "Define a maximum number of iterations. If the cost function converges it will stop sooner."}}, {"pk": 670, "model": "workflows.abstractinput", "fields": {"widget": 298, "name": "Gzipped data", "short_name": "zip", "uid": "d62fc126-afda-4f0b-876d-5180cd409779", "default": "", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "data_type", "parameter": true, "order": 3, "description": "Select if specified URLs point to data in gzipped format."}}, {"pk": 686, "model": "workflows.abstractinput", "fields": {"widget": 302, "name": "Trees per subset", "short_name": "tps", "uid": "a0b28dbe-1cb8-4987-958e-e4d379c8d2ff", "default": "20", "required": true, "multi": false, "parameter_type": "text", "variable": "trees_per_subset", "parameter": true, "order": 3, "description": "Number of trees per subset of data"}}, {"pk": 693, "model": "workflows.abstractinput", "fields": {"widget": 304, "name": "Log probabilities", "short_name": "log", "uid": "ad2231df-eef5-44b4-8a60-50f855a28fcb", "default": "", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "log_probs", "parameter": true, "order": 3, "description": "Calculate logarithm probabilities."}}, {"pk": 702, "model": "workflows.abstractinput", "fields": {"widget": 307, "name": "Trees per subset", "short_name": "tps", "uid": "8770ace6-4968-47cf-b7cc-4ad8bfff303c", "default": "20", "required": true, "multi": false, "parameter_type": "text", "variable": "trees_per_subset", "parameter": true, "order": 3, "description": "Number of trees per subset of data"}}, {"pk": 709, "model": "workflows.abstractinput", "fields": {"widget": 308, "name": "Max tree nodes", "short_name": "mtn", "uid": "a91f5676-5c91-420a-b731-5cf60afd601b", "default": "20", "required": true, "multi": false, "parameter_type": "text", "variable": "tree_nodes", "parameter": true, "order": 3, "description": "Max. number of decision tree nodes."}}, {"pk": 716, "model": "workflows.abstractinput", "fields": {"widget": 310, "name": "Max number of iterations", "short_name": "itr", "uid": "a8ec22c5-199b-43ff-9c72-780a49d57ea4", "default": "10", "required": true, "multi": false, "parameter_type": "text", "variable": "itr", "parameter": true, "order": 3, "description": ""}}, {"pk": 720, "model": "workflows.abstractinput", "fields": {"widget": 311, "name": "Tau", "short_name": "tau", "uid": "ec1391de-af20-4921-876c-d304a6a4e721", "default": "1", "required": true, "multi": false, "parameter_type": "text", "variable": "tau", "parameter": true, "order": 3, "description": "Parameter Tau controls how quickly the weight of a training example falls off with distance of its x(i) from the query point x"}}, {"pk": 721, "model": "workflows.abstractinput", "fields": {"widget": 312, "name": "m", "short_name": "m", "uid": "48392fb5-a666-4d71-ae2d-21e663e05e0b", "default": "0", "required": false, "multi": false, "parameter_type": "text", "variable": "m", "parameter": true, "order": 3, "description": "Laplace Smoothing parameter."}}, {"pk": 729, "model": "workflows.abstractinput", "fields": {"widget": 314, "name": "Random forest - difference", "short_name": "dff", "uid": "d979ff23-eb11-40cf-9d81-2a71ddf5d790", "default": "0.3", "required": true, "multi": false, "parameter_type": "text", "variable": "diff", "parameter": true, "order": 3, "description": "Random forest calculates difference in probability between most and second most probable prediction. If difference is greater than parameter diff, it outputs prediction. If a test sample is hard to predict (difference is never higher than diff), it queries whole ensemble to make a prediction."}}, {"pk": 737, "model": "workflows.abstractinput", "fields": {"widget": 321, "name": "Text", "short_name": "txt", "uid": "29a4d41b-1361-4b20-b3b2-9ecbab156ca4", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "text", "parameter": true, "order": 3, "description": "Searches for data that contain this word in this field. Do not use sentences, write only a single word."}}, {"pk": 63, "model": "workflows.abstractinput", "fields": {"widget": 40, "name": "PAGE test weight", "short_name": "wpa", "uid": "34611127-924e-4f1d-a079-8dc29519793d", "default": "1.0", "required": false, "multi": false, "parameter_type": "text", "variable": "weightPAGE", "parameter": true, "order": 4, "description": "PAGE test weight"}}, {"pk": 89, "model": "workflows.abstractinput", "fields": {"widget": 43, "name": "PAGE test weight", "short_name": "wpa", "uid": "c6a45b3a-5e84-453a-ac4a-e18898a5218f", "default": "1.0", "required": false, "multi": false, "parameter_type": "text", "variable": "weightPAGE", "parameter": true, "order": 4, "description": "PAGE test weight"}}, {"pk": 100, "model": "workflows.abstractinput", "fields": {"widget": 44, "name": "Lower bound", "short_name": "lb", "uid": "d2c9ff0d-46ea-44d1-b962-7108e44cbfb8", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "lower", "parameter": true, "order": 4, "description": "lower bound for cutoff"}}, {"pk": 113, "model": "workflows.abstractinput", "fields": {"widget": 55, "name": "Single component", "short_name": "scm", "uid": "1b27100e-c585-47f0-a30f-05d2d2720927", "default": "", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "singleComponent", "parameter": true, "order": 4, "description": "Single component"}}, {"pk": 136, "model": "workflows.abstractinput", "fields": {"widget": 57, "name": "PAGE test weight", "short_name": "wpa", "uid": "f9a9b5d6-f6d6-4d53-abac-bd67d12bb939", "default": "1.0", "required": false, "multi": false, "parameter_type": "text", "variable": "weightPAGE", "parameter": true, "order": 4, "description": "PAGE test weight"}}, {"pk": 141, "model": "workflows.abstractinput", "fields": {"widget": 59, "name": "Max nodes", "short_name": "mxn", "uid": "97f71cb5-1ff0-45dc-84ed-2afe8e3aa7fa", "default": "0", "required": false, "multi": false, "parameter_type": "text", "variable": "maxNodes", "parameter": true, "order": 4, "description": "Max nodes"}}, {"pk": 145, "model": "workflows.abstractinput", "fields": {"widget": 61, "name": "Max nodes", "short_name": "mxn", "uid": "1942dd52-a553-460b-bdba-4ef29b6a402c", "default": "0", "required": false, "multi": false, "parameter_type": "text", "variable": "maxNodes", "parameter": true, "order": 4, "description": "Max nodes"}}, {"pk": 171, "model": "workflows.abstractinput", "fields": {"widget": 72, "name": "Post-processing", "short_name": "pst", "uid": "b9d70de4-156d-45da-aece-5adf08122a5c", "default": "false", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "postprocess", "parameter": true, "order": 4, "description": "Apply post processing"}}, {"pk": 176, "model": "workflows.abstractinput", "fields": {"widget": 73, "name": "Language", "short_name": "lan", "uid": "30b3d767-220d-4de1-bbc8-3ea22abd9ec5", "default": "en", "required": true, "multi": false, "parameter_type": "select", "variable": "lang", "parameter": true, "order": 4, "description": "Language"}}, {"pk": 184, "model": "workflows.abstractinput", "fields": {"widget": 74, "name": "Pre-defined patterns", "short_name": "pat", "uid": "65d538aa-c277-4cb3-8f37-87d02ee5ede0", "default": "begin_novar", "required": false, "multi": false, "parameter_type": "select", "variable": "pattern", "parameter": true, "order": 4, "description": "Pre-defined patterns"}}, {"pk": 203, "model": "workflows.abstractinput", "fields": {"widget": 82, "name": "XML output", "short_name": "xml", "uid": "52b80a99-9302-4816-88ed-a5e1def8822d", "default": "false", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "xml", "parameter": true, "order": 4, "description": "Output results as XML"}}, {"pk": 214, "model": "workflows.abstractinput", "fields": {"widget": 83, "name": "relation", "short_name": "rel", "uid": "d22cec50-3393-4e9b-8ef3-228e959dc574", "default": "", "required": false, "multi": true, "parameter_type": null, "variable": "relation", "parameter": false, "order": 4, "description": "extra relations"}}, {"pk": 218, "model": "workflows.abstractinput", "fields": {"widget": 84, "name": "Minimum frequency", "short_name": "mfr", "uid": "21261080-c05e-4ca5-8a3f-d3fcfa9cd429", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "minimum_frequency", "parameter": true, "order": 4, "description": "Minimum frequency"}}, {"pk": 227, "model": "workflows.abstractinput", "fields": {"widget": 85, "name": "other_tables", "short_name": "lot", "uid": "72854a26-f7bf-46a3-988e-61caaeabdc7a", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "other_tables", "parameter": false, "order": 4, "description": "List of Orange data tables"}}, {"pk": 237, "model": "workflows.abstractinput", "fields": {"widget": 87, "name": "b", "short_name": "b", "uid": "2ec81e9e-d911-46a1-a95d-2eaf349443a8", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "b", "parameter": false, "order": 4, "description": "background knowledge"}}, {"pk": 248, "model": "workflows.abstractinput", "fields": {"widget": 88, "name": "neg", "short_name": "neg", "uid": "0b46921d-50fe-46b1-a1e4-67c918160a7f", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "neg", "parameter": false, "order": 4, "description": "negative examples"}}, {"pk": 255, "model": "workflows.abstractinput", "fields": {"widget": 88, "name": "negation", "short_name": "neg", "uid": "bfff50a5-ed9b-4e3f-bfb0-e6d135a60f38", "default": "none", "required": false, "multi": false, "parameter_type": "select", "variable": "negation", "parameter": true, "order": 4, "description": "One of now, later, none.\r\nnow: To features generated by featurize.pl, process.pl\r\nwill also add their versions where the complete body is\r\nnegated. (Negations of individual literals can be done by\r\nsuitably defining background knowledge predicates.)\r\nlater: tells the program that an inducer capable of\r\nnegating features will be applied on the propositionalized\r\nrepresentation. This influences functions described below."}}, {"pk": 264, "model": "workflows.abstractinput", "fields": {"widget": 89, "name": "ont2", "short_name": "ont", "uid": "3b0d4d2e-177e-4054-81d1-a841f4761f94", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "ont2", "parameter": false, "order": 4, "description": ""}}, {"pk": 285, "model": "workflows.abstractinput", "fields": {"widget": 91, "name": "Instances", "short_name": "ins", "uid": "91c0ad22-1d1b-4f0b-8ea9-be94be1ade29", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "instances", "parameter": false, "order": 4, "description": ""}}, {"pk": 294, "model": "workflows.abstractinput", "fields": {"widget": 94, "name": "Class index", "short_name": "cla", "uid": "1e067896-7006-4b44-82af-b03a61727080", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "class_index", "parameter": true, "order": 4, "description": ""}}, {"pk": 304, "model": "workflows.abstractinput", "fields": {"widget": 97, "name": "Instances", "short_name": "ins", "uid": "da953155-8ed2-416b-b739-bed4fd748dda", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "instances", "parameter": false, "order": 4, "description": "to be used by the provided learner to create a clusterer."}}, {"pk": 319, "model": "workflows.abstractinput", "fields": {"widget": 101, "name": "Instances", "short_name": "ins", "uid": "c22197af-f60b-4b76-b40e-516c17c9e1ab", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "instances", "parameter": false, "order": 4, "description": "to be classified.\r\n\r\nProvided by:\r\nArff to Weka Instances"}}, {"pk": 321, "model": "workflows.abstractinput", "fields": {"widget": 102, "name": "Instances", "short_name": "ins", "uid": "1c36937f-7127-48a5-b086-ab3356e8db7d", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "instances", "parameter": false, "order": 4, "description": "to be used by the provided learner to create a classifier.\r\n\r\nProvided by:\r\nArff to Weka Instances"}}, {"pk": 324, "model": "workflows.abstractinput", "fields": {"widget": 103, "name": "instances", "short_name": "ins", "uid": "5d68936c-6cfc-446e-95e7-2c3173a6232c", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "instances", "parameter": false, "order": 4, "description": ""}}, {"pk": 346, "model": "workflows.abstractinput", "fields": {"widget": 109, "name": "original_training_instances", "short_name": "ori", "uid": "e7f4e700-08b6-4568-91aa-e06937d5e8d7", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "original_training_instances", "parameter": false, "order": 4, "description": ""}}, {"pk": 348, "model": "workflows.abstractinput", "fields": {"widget": 110, "name": "Instances", "short_name": "ins", "uid": "278891e3-2530-4c9b-9871-57e6b6ad4070", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "instances", "parameter": false, "order": 4, "description": "Provided data."}}, {"pk": 352, "model": "workflows.abstractinput", "fields": {"widget": 111, "name": "original_training_instances", "short_name": "ori", "uid": "130682bd-fea0-405f-ad15-48a8a8f07bae", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "original_training_instances", "parameter": false, "order": 4, "description": ""}}, {"pk": 403, "model": "workflows.abstractinput", "fields": {"widget": 140, "name": "margin", "short_name": "mrg", "uid": "1cce36a4-167d-4a23-83ee-eae626a3b492", "default": "0.0", "required": false, "multi": false, "parameter_type": "text", "variable": "margin", "parameter": true, "order": 4, "description": ""}}, {"pk": 421, "model": "workflows.abstractinput", "fields": {"widget": 150, "name": "List of F-measures", "short_name": "f", "uid": "706ba66d-3425-4093-815f-8c62cc034e5b", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "f", "parameter": false, "order": 4, "description": ""}}, {"pk": 431, "model": "workflows.abstractinput", "fields": {"widget": 156, "name": "Number of repetitions", "short_name": "rep", "uid": "da5ab14e-9e1c-4395-b6ce-8ff0d53de4c9", "default": "100", "required": false, "multi": false, "parameter_type": "text", "variable": "times", "parameter": true, "order": 4, "description": ""}}, {"pk": 445, "model": "workflows.abstractinput", "fields": {"widget": 166, "name": "Cut-off points", "short_name": "cp", "uid": "43b2e055-65c1-4cc3-ae94-926b71911c0e", "default": "", "required": false, "multi": false, "parameter_type": "textarea", "variable": "points", "parameter": true, "order": 4, "description": "Comma separated cut-off points"}}, {"pk": 469, "model": "workflows.abstractinput", "fields": {"widget": 178, "name": "database", "short_name": "db", "uid": "d132adce-c3ec-411a-8ee7-906be4a99f61", "default": "", "required": true, "multi": false, "parameter_type": "text", "variable": "database", "parameter": true, "order": 4, "description": ""}}, {"pk": 472, "model": "workflows.abstractinput", "fields": {"widget": 179, "name": "features", "short_name": "frs", "uid": "d96f84a3-69d9-45f5-9f1e-5041e736bb2c", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "features", "parameter": false, "order": 4, "description": "domain features"}}, {"pk": 477, "model": "workflows.abstractinput", "fields": {"widget": 181, "name": "features", "short_name": "frs", "uid": "9c245a66-c419-44aa-a077-d133c8b2e5f5", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "features", "parameter": false, "order": 4, "description": "domain features"}}, {"pk": 485, "model": "workflows.abstractinput", "fields": {"widget": 183, "name": "features", "short_name": "frs", "uid": "bdba5268-fa34-40c6-9416-aa9c5f7636ac", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "features", "parameter": false, "order": 4, "description": "domain features"}}, {"pk": 514, "model": "workflows.abstractinput", "fields": {"widget": 202, "name": "multi_class", "short_name": "par", "uid": "da13b053-3d1b-48ad-a046-5683143f1391", "default": "ovr", "required": false, "multi": false, "parameter_type": "select", "variable": "classIn", "parameter": true, "order": 4, "description": ""}}, {"pk": 528, "model": "workflows.abstractinput", "fields": {"widget": 210, "name": "Consumer Key", "short_name": "ck", "uid": "ed2db381-2ed2-4a4d-bd6d-9f9dc0430a50", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "ck", "parameter": true, "order": 4, "description": "Go to http://dev.twitter.com and create an app. The consumer key and secret will be generated for you after."}}, {"pk": 545, "model": "workflows.abstractinput", "fields": {"widget": 223, "name": "Number of tweets for hand-labeling chosen with the random query strategy.", "short_name": "q2", "uid": "216ae867-a808-47f4-a233-052d62f09dd8", "default": "2", "required": false, "multi": false, "parameter_type": "text", "variable": "q_strategy_random", "parameter": true, "order": 4, "description": "Number of tweets for hand-labeling chosen with the random query strategy"}}, {"pk": 571, "model": "workflows.abstractinput", "fields": {"widget": 245, "name": "Inhibition", "short_name": "inh", "uid": "17545bf5-42d0-44ec-8c20-734031a85dc4", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "inhibition", "parameter": false, "order": 4, "description": "CSV file with inhibitions."}}, {"pk": 600, "model": "workflows.abstractinput", "fields": {"widget": 259, "name": "Number of Folds for Cross-Validation", "short_name": "kfl", "uid": "e70d523f-e740-4d69-a0be-fed6b8ec0ba9", "default": "10", "required": true, "multi": false, "parameter_type": "select", "variable": "k_folds", "parameter": true, "order": 4, "description": ""}}, {"pk": 627, "model": "workflows.abstractinput", "fields": {"widget": 276, "name": "Target class", "short_name": "cls", "uid": "1c10f750-03f5-4640-8641-0059c7dc902f", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "target", "parameter": false, "order": 4, "description": ""}}, {"pk": 672, "model": "workflows.abstractinput", "fields": {"widget": 298, "name": "Attribute selection", "short_name": "ind", "uid": "e32184e0-f38a-466f-a991-82e084a1cd8b", "default": "", "required": true, "multi": false, "parameter_type": "text", "variable": "X_indices", "parameter": true, "order": 4, "description": "Select attributes that will processed. \r\n\r\nExample: 1 - 10 for indices in the range from 1 to 10 or 1,2 for indices 1 and 2."}}, {"pk": 682, "model": "workflows.abstractinput", "fields": {"widget": 302, "name": "Max tree nodes", "short_name": "mnt", "uid": "5a915d8b-2c99-4661-aa20-325709b61b6b", "default": "20", "required": true, "multi": false, "parameter_type": "text", "variable": "tree_nodes", "parameter": true, "order": 4, "description": "Max. number of decision tree nodes"}}, {"pk": 701, "model": "workflows.abstractinput", "fields": {"widget": 307, "name": "Max tree nodes", "short_name": "mnt", "uid": "3d48b0d0-a304-45d5-9d18-3ca17e8fcf05", "default": "20", "required": true, "multi": false, "parameter_type": "text", "variable": "tree_nodes", "parameter": true, "order": 4, "description": "Max. number of decision tree nodes"}}, {"pk": 710, "model": "workflows.abstractinput", "fields": {"widget": 308, "name": "Min samples split", "short_name": "lmi", "uid": "cde1d8a0-c312-4497-a07b-43f7cd7f95e2", "default": "5", "required": true, "multi": false, "parameter_type": "text", "variable": "leaf_min_inst", "parameter": true, "order": 4, "description": "Min. number of samples to split the node"}}, {"pk": 714, "model": "workflows.abstractinput", "fields": {"widget": 310, "name": "Random state", "short_name": "rsd", "uid": "47bb296e-f481-432f-a381-63c6df4c6950", "default": "None", "required": true, "multi": false, "parameter_type": "text", "variable": "seed", "parameter": true, "order": 4, "description": "Define a random state"}}, {"pk": 727, "model": "workflows.abstractinput", "fields": {"widget": 314, "name": "Random forest  - random state", "short_name": "rds", "uid": "8ec2b906-2b9e-4cda-9455-09ccd7d134fb", "default": "None", "required": true, "multi": false, "parameter_type": "text", "variable": "seed", "parameter": true, "order": 4, "description": "Define a random state for predict phase."}}, {"pk": 738, "model": "workflows.abstractinput", "fields": {"widget": 321, "name": "MinWeight", "short_name": "wgt", "uid": "2d591bb7-6838-4f0b-8cdc-1d6ed5bfd0d7", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "minweight", "parameter": true, "order": 4, "description": "Input must be an integer or double. Filters for edges whose weight is at least weight."}}, {"pk": 71, "model": "workflows.abstractinput", "fields": {"widget": 40, "name": "Fisher test weight", "short_name": "wfi", "uid": "bbf0e48b-2d0c-460a-bb91-c4fa3efc6576", "default": "0.0", "required": false, "multi": false, "parameter_type": "text", "variable": "weightFisher", "parameter": true, "order": 5, "description": "Fisher test weight"}}, {"pk": 80, "model": "workflows.abstractinput", "fields": {"widget": 43, "name": "Fisher test weight", "short_name": "wfi", "uid": "236ba7db-5f80-4a25-ab08-3a7b81a501b9", "default": "0.0", "required": false, "multi": false, "parameter_type": "text", "variable": "weightFisher", "parameter": true, "order": 5, "description": "Fisher test weight"}}, {"pk": 97, "model": "workflows.abstractinput", "fields": {"widget": 44, "name": "Absolute", "short_name": "abs", "uid": "1a9e6e81-0484-4819-97aa-7485ff625da5", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "absolute", "parameter": true, "order": 5, "description": "absolute or not"}}, {"pk": 118, "model": "workflows.abstractinput", "fields": {"widget": 55, "name": "Max nodes", "short_name": "mxn", "uid": "ff95b75f-b4f4-4b3e-acf2-d69aa41ed948", "default": "0", "required": false, "multi": false, "parameter_type": "text", "variable": "maxNodes", "parameter": true, "order": 5, "description": "Max nodes"}}, {"pk": 120, "model": "workflows.abstractinput", "fields": {"widget": 57, "name": "Fisher test weight", "short_name": "wfi", "uid": "0ecfe685-2bed-4110-821a-51c465099094", "default": "0.0", "required": false, "multi": false, "parameter_type": "text", "variable": "weightFisher", "parameter": true, "order": 5, "description": "Fisher test weight"}}, {"pk": 138, "model": "workflows.abstractinput", "fields": {"widget": 59, "name": "Medoids", "short_name": "mds", "uid": "078c052f-2303-44dc-b1e4-4f39b0839b55", "default": "", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "medoids", "parameter": true, "order": 5, "description": "Medoids"}}, {"pk": 148, "model": "workflows.abstractinput", "fields": {"widget": 61, "name": "Start nodes", "short_name": "beg", "uid": "c68a9f13-92a1-4000-ae7d-bcf43311109e", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "startNodes", "parameter": false, "order": 5, "description": "Start nodes"}}, {"pk": 172, "model": "workflows.abstractinput", "fields": {"widget": 72, "name": "Bohoricica", "short_name": "boh", "uid": "f429eb2c-a5ac-44b8-a691-602c97a2b0da", "default": "false", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "bohoricica", "parameter": true, "order": 5, "description": "Bohoricica"}}, {"pk": 174, "model": "workflows.abstractinput", "fields": {"widget": 73, "name": "Terms per sentence", "short_name": "tps", "uid": "14b2d90f-4539-4c67-94ea-2636988adc86", "default": "3", "required": true, "multi": false, "parameter_type": "text", "variable": "terms_per_sentence", "parameter": true, "order": 5, "description": "Terms per sentence"}}, {"pk": 202, "model": "workflows.abstractinput", "fields": {"widget": 82, "name": "Post-processing", "short_name": "pst", "uid": "4bd34d04-8dd4-4a66-8005-12aa7df88c92", "default": "false", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "postprocess", "parameter": true, "order": 5, "description": "Apply post processing"}}, {"pk": 210, "model": "workflows.abstractinput", "fields": {"widget": 83, "name": "positive class val", "short_name": "pcl", "uid": "ad84f724-9935-4a3a-90b2-a4af70721477", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "posClassVal", "parameter": true, "order": 5, "description": "positive class value"}}, {"pk": 221, "model": "workflows.abstractinput", "fields": {"widget": 84, "name": "Maximum size of features (applies to HiFi and Poly algs)", "short_name": "msf", "uid": "88122964-dd6b-4d90-ab97-ee865c454cbc", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "maximum_size", "parameter": true, "order": 5, "description": "Maximum size of features (applies to HiFi and Poly algs)"}}, {"pk": 228, "model": "workflows.abstractinput", "fields": {"widget": 85, "name": "context", "short_name": "ctx", "uid": "8f02978b-e0d7-45c5-ab74-6a0e8728654d", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "context", "parameter": false, "order": 5, "description": "Context"}}, {"pk": 245, "model": "workflows.abstractinput", "fields": {"widget": 87, "name": "settings", "short_name": "set", "uid": "bfe16b08-89b1-4835-875c-6b0302fb1da3", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "settings", "parameter": false, "order": 5, "description": "settings facts"}}, {"pk": 247, "model": "workflows.abstractinput", "fields": {"widget": 88, "name": "min_coverage", "short_name": "mcv", "uid": "0864df0d-3e46-4af2-9ea3-2ccbfe33034a", "default": "1", "required": false, "multi": false, "parameter_type": "text", "variable": "min_coverage", "parameter": true, "order": 5, "description": "An integer mc. All features (including negated versions)\r\ncovering fewer than mc instances will be discarded.\r\nHowever, if negation is later (see above), a feature\r\nis discarded only if both (a) coverage thereof and (b) the\r\ncoverage of its negated version are smaller than mc."}}, {"pk": 253, "model": "workflows.abstractinput", "fields": {"widget": 88, "name": "settings", "short_name": "set", "uid": "a1660c9f-952d-4f29-9f23-9b0be5fe8cea", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "settings", "parameter": false, "order": 5, "description": "settings"}}, {"pk": 268, "model": "workflows.abstractinput", "fields": {"widget": 89, "name": "ont1", "short_name": "ont", "uid": "5a86e8aa-9230-4bd3-80f2-3b2bc2ebc2b8", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "ont1", "parameter": false, "order": 5, "description": ""}}, {"pk": 283, "model": "workflows.abstractinput", "fields": {"widget": 91, "name": "Folds", "short_name": "fol", "uid": "1a99446a-c3bd-40b4-996a-eb1af12fbf65", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "folds", "parameter": true, "order": 5, "description": ""}}, {"pk": 344, "model": "workflows.abstractinput", "fields": {"widget": 109, "name": "instances", "short_name": "ins", "uid": "77403ebd-7c9b-43c7-a2c7-95087c621eb2", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "instances", "parameter": false, "order": 5, "description": ""}}, {"pk": 355, "model": "workflows.abstractinput", "fields": {"widget": 111, "name": "instances", "short_name": "ins", "uid": "f03406cb-272d-4b4b-a17b-c7c5a8b0b9df", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "instances", "parameter": false, "order": 5, "description": ""}}, {"pk": 525, "model": "workflows.abstractinput", "fields": {"widget": 210, "name": "Consumer Secret", "short_name": "cs", "uid": "9b9d6268-675a-46c5-82d5-b143e5fdd326", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "cs", "parameter": true, "order": 5, "description": ""}}, {"pk": 577, "model": "workflows.abstractinput", "fields": {"widget": 245, "name": "Binding", "short_name": "bnd", "uid": "eac8c9d4-a0ab-414e-a083-54a5f860e031", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "binding", "parameter": false, "order": 5, "description": "CSV file with bindings."}}, {"pk": 668, "model": "workflows.abstractinput", "fields": {"widget": 298, "name": "Attribute metadata", "short_name": "mta", "uid": "705b4459-6f05-4fd3-a230-33e0ddd784b3", "default": "numeric", "required": true, "multi": false, "parameter_type": "select", "variable": "atr_meta", "parameter": true, "order": 5, "description": "Select numeric, if all attributes are numeric or discrete, if all attributes are discrete. \r\n"}}, {"pk": 687, "model": "workflows.abstractinput", "fields": {"widget": 302, "name": "Min samples split", "short_name": "lmi", "uid": "a2f366a9-af74-4b3f-90ed-33c1fcad4c3a", "default": "5", "required": true, "multi": false, "parameter_type": "text", "variable": "leaf_min_inst", "parameter": true, "order": 5, "description": "Min. number of samples to split the node"}}, {"pk": 704, "model": "workflows.abstractinput", "fields": {"widget": 307, "name": "Min samples split", "short_name": "lmi", "uid": "ac032f38-f4a4-44ea-8c02-96506d4f8e86", "default": "5", "required": true, "multi": false, "parameter_type": "text", "variable": "leaf_min_inst", "parameter": true, "order": 5, "description": "Min. number of samples to split the node"}}, {"pk": 711, "model": "workflows.abstractinput", "fields": {"widget": 308, "name": "Class majority", "short_name": "csm", "uid": "f31f0f86-238b-4ce1-b7e7-1ad6e88f55b0", "default": "1", "required": true, "multi": false, "parameter_type": "text", "variable": "majority", "parameter": true, "order": 5, "description": "Purity of a subset."}}, {"pk": 725, "model": "workflows.abstractinput", "fields": {"widget": 314, "name": "Dataset", "short_name": "dst", "uid": "0c174cfd-0d61-44ff-8ce2-9c32f8791293", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "dataset", "parameter": false, "order": 5, "description": "dataset"}}, {"pk": 62, "model": "workflows.abstractinput", "fields": {"widget": 40, "name": "Use molecular functions ontology", "short_name": "mol", "uid": "33818966-bd90-4694-99bb-c6ccd4d5d96c", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "useMolecularFunctions", "parameter": true, "order": 6, "description": "Use molecular functions ontology"}}, {"pk": 92, "model": "workflows.abstractinput", "fields": {"widget": 43, "name": "Use molecular functions ontology", "short_name": "mol", "uid": "d391bdf5-38b5-4e3e-8a6d-ad8ceabefcea", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "useMolecularFunctions", "parameter": true, "order": 6, "description": "Use molecular functions ontology"}}, {"pk": 116, "model": "workflows.abstractinput", "fields": {"widget": 55, "name": "Medoids", "short_name": "mds", "uid": "aecdd58f-1fef-4aec-8039-2fdbc4cc7279", "default": "", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "medoids", "parameter": true, "order": 6, "description": "Medoids"}}, {"pk": 135, "model": "workflows.abstractinput", "fields": {"widget": 57, "name": "Use molecular functions ontology", "short_name": "mol", "uid": "f0349a66-56c0-4de6-985f-b9d2ed6b0232", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "useMolecularFunctions", "parameter": true, "order": 6, "description": "Use molecular functions ontology"}}, {"pk": 139, "model": "workflows.abstractinput", "fields": {"widget": 59, "name": "Start nodes", "short_name": "beg", "uid": "14241e7b-e316-446b-b795-b5a8038769ee", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "startNodes", "parameter": false, "order": 6, "description": "Start nodes"}}, {"pk": 167, "model": "workflows.abstractinput", "fields": {"widget": 72, "name": "Antique slovenian", "short_name": "atq", "uid": "161bece4-5e34-4f47-821c-ffbb35f6069a", "default": "false", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "antique", "parameter": true, "order": 6, "description": "Antique slovenian"}}, {"pk": 183, "model": "workflows.abstractinput", "fields": {"widget": 73, "name": "Nominatives (only for slovene)", "short_name": "nom", "uid": "eaf18ca7-b87c-4f78-90c1-a93837d0b525", "default": "0", "required": true, "multi": false, "parameter_type": "select", "variable": "nominatives", "parameter": true, "order": 6, "description": "Nominatives"}}, {"pk": 200, "model": "workflows.abstractinput", "fields": {"widget": 82, "name": "Bohoricica", "short_name": "boh", "uid": "10af1284-dba8-4bdb-9b81-a479f0ce07cb", "default": "false", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "bohoricica", "parameter": true, "order": 6, "description": "Bohoricica"}}, {"pk": 207, "model": "workflows.abstractinput", "fields": {"widget": 83, "name": "cutoff", "short_name": "cut", "uid": "0e5b7e98-aaa2-481d-b2d1-5b339a05b754", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "cutoff", "parameter": true, "order": 6, "description": "cutoff point for unlabeled data"}}, {"pk": 222, "model": "workflows.abstractinput", "fields": {"widget": 84, "name": "Covered class (applies only to the RelF algorithm)", "short_name": "ccl", "uid": "a225e421-e8f1-4a79-a78b-98f7d09d34df", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "covered_class", "parameter": true, "order": 6, "description": "Covered class (applies only to the RelF algorithm)"}}, {"pk": 226, "model": "workflows.abstractinput", "fields": {"widget": 85, "name": "Inverse Document Frequencies", "short_name": "idf", "uid": "3a9a9e51-9ad2-4d6a-880a-8145b824a32b", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "idf", "parameter": false, "order": 6, "description": "Inverse Document Frequencies which will be used for feature calculation."}}, {"pk": 246, "model": "workflows.abstractinput", "fields": {"widget": 87, "name": "minpos", "short_name": "mps", "uid": "cdeaa39a-7eeb-40eb-9443-8519cb841d2e", "default": "1", "required": false, "multi": false, "parameter_type": "text", "variable": "minpos", "parameter": true, "order": 6, "description": "Set a lower bound on the number of positive examples to be covered by an acceptable clause. If the best clause covers positive examples below this number, then it is not added to the current theory. This can be used to prevent Aleph from adding ground unit clauses to the theory (by setting the value to 2)."}}, {"pk": 257, "model": "workflows.abstractinput", "fields": {"widget": 88, "name": "filtering", "short_name": "flt", "uid": "f510c2a1-454f-4ef8-b346-aba39a41ce24", "default": "true", "required": false, "multi": false, "parameter_type": "select", "variable": "flt", "parameter": true, "order": 6, "description": "One of true, false. If true, each feature will be discarded\r\nif (a) it covers the same set of instances as some previously\r\nconstructed feature, or (b) it covers all instances."}}, {"pk": 260, "model": "workflows.abstractinput", "fields": {"widget": 89, "name": "generalTerms", "short_name": "gen", "uid": "141f075c-3634-4d6e-8254-fd9afbaa0eb7", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "generalTerms", "parameter": false, "order": 6, "description": ""}}, {"pk": 526, "model": "workflows.abstractinput", "fields": {"widget": 210, "name": "Access Token", "short_name": "at", "uid": "a951f2d1-c2d1-40b3-afe9-799195e03aa0", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "at", "parameter": true, "order": 6, "description": ""}}, {"pk": 576, "model": "workflows.abstractinput", "fields": {"widget": 245, "name": "Activation passive", "short_name": "acp", "uid": "e59a900a-1796-43ba-a229-e0b82c4ef964", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "activation_passive", "parameter": false, "order": 6, "description": "CSV file with passive forms of activation."}}, {"pk": 666, "model": "workflows.abstractinput", "fields": {"widget": 298, "name": "Metadata URL", "short_name": "cmt", "uid": "491eab89-b3f1-4503-864b-7cad9a01dda7", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "custom", "parameter": true, "order": 6, "description": "Define an URL of a file with attribute metadata.\r\n\r\nExample of a file with 3 attributes, where first and second are continous and third is discrete:\r\natr1, atr2, atr3\r\nc,c,d "}}, {"pk": 688, "model": "workflows.abstractinput", "fields": {"widget": 302, "name": "Class majority", "short_name": "csm", "uid": "fe7f5d5a-c2e2-4ae9-b138-18b1de7c4e93", "default": "1", "required": true, "multi": false, "parameter_type": "text", "variable": "majority", "parameter": true, "order": 6, "description": "Purity of a subset."}}, {"pk": 698, "model": "workflows.abstractinput", "fields": {"widget": 307, "name": "Class majority", "short_name": "csm", "uid": "1b23ead1-b104-4d27-a6fd-b23de6efa28f", "default": "1", "required": true, "multi": false, "parameter_type": "text", "variable": "majority", "parameter": true, "order": 6, "description": "Purity of a subset."}}, {"pk": 707, "model": "workflows.abstractinput", "fields": {"widget": 308, "name": "Measure", "short_name": "msr", "uid": "28f53666-76b0-4d44-acab-0824e603a848", "default": "info_gain", "required": true, "multi": false, "parameter_type": "select", "variable": "measure", "parameter": true, "order": 6, "description": "Select measure for estimation of attributes."}}, {"pk": 74, "model": "workflows.abstractinput", "fields": {"widget": 40, "name": "Summarize descriptions", "short_name": "sde", "uid": "d0c36c9f-d6b7-480b-b6e0-965050b0bb3a", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "summarizeDescriptions", "parameter": true, "order": 7, "description": "Summarize descriptions"}}, {"pk": 87, "model": "workflows.abstractinput", "fields": {"widget": 43, "name": "Summarize descriptions", "short_name": "sde", "uid": "ba4f3848-3f51-4bf8-afc5-9c6687b099ca", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "summarizeDescriptions", "parameter": true, "order": 7, "description": "Summarize descriptions"}}, {"pk": 112, "model": "workflows.abstractinput", "fields": {"widget": 55, "name": "Start nodes", "short_name": "beg", "uid": "0bb9e00a-2159-419c-8a3a-758d8ae778d1", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "startNodes", "parameter": false, "order": 7, "description": "Start nodes"}}, {"pk": 123, "model": "workflows.abstractinput", "fields": {"widget": 57, "name": "Summarize descriptions", "short_name": "sde", "uid": "28ee1f37-9ed8-4f95-bb9b-4f1b0791c207", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "summarizeDescriptions", "parameter": true, "order": 7, "description": "Summarize descriptions"}}, {"pk": 180, "model": "workflows.abstractinput", "fields": {"widget": 73, "name": "Threshold top % terms", "short_name": "thr", "uid": "ba6fb908-5d5b-4af7-afc4-5adbe5fd5d97", "default": "2%", "required": true, "multi": false, "parameter_type": "text", "variable": "threshold", "parameter": true, "order": 7, "description": "Threshold"}}, {"pk": 204, "model": "workflows.abstractinput", "fields": {"widget": 82, "name": "Antique slovenian", "short_name": "atq", "uid": "57f45eb8-8fae-4ca1-ae36-178c364de2a7", "default": "false", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "antique", "parameter": true, "order": 7, "description": "Antique slovenian"}}, {"pk": 211, "model": "workflows.abstractinput", "fields": {"widget": 83, "name": "minimum TP", "short_name": "min", "uid": "b2bbe491-8cf3-4ec7-b7a5-f52426ab9285", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "minPos", "parameter": true, "order": 7, "description": "min TP examples per rule"}}, {"pk": 219, "model": "workflows.abstractinput", "fields": {"widget": 84, "name": "Use sampling ", "short_name": "smp", "uid": "755563cb-3640-4737-b766-9e6db0f6a14d", "default": "false", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "use_sampling", "parameter": true, "order": 7, "description": "Use sampling mode"}}, {"pk": 242, "model": "workflows.abstractinput", "fields": {"widget": 87, "name": "noise", "short_name": "noi", "uid": "61292a9b-ff5b-4a7e-8baf-e6810cb50dcd", "default": "0", "required": false, "multi": false, "parameter_type": "text", "variable": "noise", "parameter": true, "order": 7, "description": "Set an upper bound on the number of negative examples allowed to be covered by an acceptable clause."}}, {"pk": 263, "model": "workflows.abstractinput", "fields": {"widget": 89, "name": "interactions", "short_name": "int", "uid": "303998af-0f97-4895-b5fb-1ec57f0ab706", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "interactions", "parameter": false, "order": 7, "description": ""}}, {"pk": 523, "model": "workflows.abstractinput", "fields": {"widget": 210, "name": "Access Token Secret", "short_name": "as", "uid": "299ae040-2916-4b88-8a79-3ced689ef23f", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "as", "parameter": true, "order": 7, "description": ""}}, {"pk": 572, "model": "workflows.abstractinput", "fields": {"widget": 245, "name": "Inhibition passive", "short_name": "inp", "uid": "29aeb4f1-d4e9-4506-b62a-6dfd2db8e029", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "inhibition_passive", "parameter": false, "order": 7, "description": "CSV file with passive forms of inhibition."}}, {"pk": 673, "model": "workflows.abstractinput", "fields": {"widget": 298, "name": "ID index", "short_name": "id", "uid": "f100a206-8fdd-4f8f-afa4-c7d3c3b6f0ca", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "id_index", "parameter": true, "order": 7, "description": "Define identifier index in the data."}}, {"pk": 684, "model": "workflows.abstractinput", "fields": {"widget": 302, "name": "Measure", "short_name": "msr", "uid": "68cbccf9-7469-4b55-b96e-4f7c6a3c9cde", "default": "info_gain", "required": true, "multi": false, "parameter_type": "select", "variable": "measure", "parameter": true, "order": 7, "description": "Select measure for estimation of attributes."}}, {"pk": 703, "model": "workflows.abstractinput", "fields": {"widget": 307, "name": "Measure", "short_name": "msr", "uid": "9a8f3c2c-265c-4b37-93c1-d58fee9dd7af", "default": "info_gain", "required": true, "multi": false, "parameter_type": "select", "variable": "measure", "parameter": true, "order": 7, "description": "Select measure for estimation of attributes."}}, {"pk": 708, "model": "workflows.abstractinput", "fields": {"widget": 308, "name": "Discretization", "short_name": "spf", "uid": "8b88d56c-6cbb-451f-a618-4a1a27993a90", "default": "equal_freq", "required": true, "multi": false, "parameter_type": "select", "variable": "split_fun", "parameter": true, "order": 7, "description": "Select equal frequency discretization or random discretization for numeric attributes"}}, {"pk": 70, "model": "workflows.abstractinput", "fields": {"widget": 40, "name": "Use biological processes ontology", "short_name": "bio", "uid": "b3089e70-9196-42a5-beea-e0f89e480694", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "useBiologicalProcesses", "parameter": true, "order": 8, "description": "Use biological processes ontology"}}, {"pk": 85, "model": "workflows.abstractinput", "fields": {"widget": 43, "name": "Use biological processes ontology", "short_name": "bio", "uid": "6215c1dc-2b3c-4691-9a36-e215ed15f385", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "useBiologicalProcesses", "parameter": true, "order": 8, "description": "Use biological processes ontology"}}, {"pk": 134, "model": "workflows.abstractinput", "fields": {"widget": 57, "name": "Use biological processes ontology", "short_name": "bio", "uid": "e276f6f7-a532-4cba-b9d6-7ffc0e5b12dc", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "useBiologicalProcesses", "parameter": true, "order": 8, "description": "Use biological processes ontology"}}, {"pk": 175, "model": "workflows.abstractinput", "fields": {"widget": 73, "name": "Verb between two terms", "short_name": "vtt", "uid": "24ce3b81-ae6d-4976-84c2-5bc56977ee8b", "default": "None", "required": false, "multi": false, "parameter_type": "select", "variable": "verb_two_terms", "parameter": true, "order": 8, "description": "Verb between two terms"}}, {"pk": 209, "model": "workflows.abstractinput", "fields": {"widget": 83, "name": "maximum FP", "short_name": "noi", "uid": "87adfb36-8ca2-4c60-b404-c81e05485e00", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "noise", "parameter": true, "order": 8, "description": "max FP examples per rule"}}, {"pk": 223, "model": "workflows.abstractinput", "fields": {"widget": 84, "name": "Sample size", "short_name": "ssz", "uid": "b0a6bd15-f1cb-4098-a551-95993ccf4c12", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "sample_size", "parameter": true, "order": 8, "description": "Sample size"}}, {"pk": 241, "model": "workflows.abstractinput", "fields": {"widget": 87, "name": "clauselength", "short_name": "cln", "uid": "546d3a62-b499-4e61-a9b1-4f89f24ba01f", "default": "4", "required": false, "multi": false, "parameter_type": "text", "variable": "clauselength", "parameter": true, "order": 8, "description": " Sets upper bound on number of literals in an acceptable clause."}}, {"pk": 272, "model": "workflows.abstractinput", "fields": {"widget": 89, "name": "maxNumTerms", "short_name": "max", "uid": "8cbf4e91-616c-4b35-a16e-86c6ca1e2dd4", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "maxNumTerms", "parameter": true, "order": 8, "description": ""}}, {"pk": 578, "model": "workflows.abstractinput", "fields": {"widget": 245, "name": "Binding passive", "short_name": "bnp", "uid": "f448d9b8-d646-4eda-9306-899942073800", "default": "", "required": true, "multi": false, "parameter_type": null, "variable": "binding_passive", "parameter": false, "order": 8, "description": "CSV file with passive forms of binding."}}, {"pk": 667, "model": "workflows.abstractinput", "fields": {"widget": 298, "name": "Class index", "short_name": "tar", "uid": "69a3061b-9dcf-4c18-9f69-b5bc082dd65e", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "y_index", "parameter": true, "order": 8, "description": "Define the class index in the dataset. If it is not defined, last attribute is used as the class."}}, {"pk": 681, "model": "workflows.abstractinput", "fields": {"widget": 302, "name": "Discretization", "short_name": "spf", "uid": "00758cdf-2eb5-43c5-bedf-bd3b8b9c29d6", "default": "equal_freq", "required": true, "multi": false, "parameter_type": "select", "variable": "split_fun", "parameter": true, "order": 8, "description": "Select equal frequency discretization or random discretization for numeric attributes"}}, {"pk": 705, "model": "workflows.abstractinput", "fields": {"widget": 307, "name": "Discretization", "short_name": "spf", "uid": "c43bfc92-e1af-42fc-8d73-f7348ebdaf40", "default": "equal_freq", "required": true, "multi": false, "parameter_type": "select", "variable": "split_fun", "parameter": true, "order": 8, "description": "Select equal frequency discretization or random discretization for numeric attributes"}}, {"pk": 65, "model": "workflows.abstractinput", "fields": {"widget": 40, "name": "Random seed", "short_name": "rnd", "uid": "8c2bd0fd-08ec-42cc-8b99-4f580e6ee1a3", "default": "-1", "required": false, "multi": false, "parameter_type": "text", "variable": "rndGenSeed", "parameter": true, "order": 9, "description": "Random seed (-1 uses current time)"}}, {"pk": 84, "model": "workflows.abstractinput", "fields": {"widget": 43, "name": "Random seed", "short_name": "rnd", "uid": "4924c08a-adc1-41d1-bf91-c3e2b8c0f786", "default": "-1", "required": false, "multi": false, "parameter_type": "text", "variable": "rndGenSeed", "parameter": true, "order": 9, "description": "Random seed (-1 uses current time)"}}, {"pk": 125, "model": "workflows.abstractinput", "fields": {"widget": 57, "name": "Random seed", "short_name": "rnd", "uid": "41a2859a-2a69-4233-999c-a4639b6493a0", "default": "-1", "required": false, "multi": false, "parameter_type": "text", "variable": "rndGenSeed", "parameter": true, "order": 9, "description": "Random seed (-1 uses current time)"}}, {"pk": 179, "model": "workflows.abstractinput", "fields": {"widget": 73, "name": "First term should be a multi-word term", "short_name": "mwt", "uid": "7b47a94d-c8c0-4264-98da-9e96d3580a1e", "default": "false", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "multiword_term", "parameter": true, "order": 9, "description": "First term should be a multi-word term"}}, {"pk": 216, "model": "workflows.abstractinput", "fields": {"widget": 83, "name": "clause length", "short_name": "cl", "uid": "f51f11b5-a9c4-43cd-a337-a9f6e6e64992", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "clauseLen", "parameter": true, "order": 9, "description": "max predicates per rule"}}, {"pk": 217, "model": "workflows.abstractinput", "fields": {"widget": 84, "name": "Max polynomial degree (applies to Poly)", "short_name": "mdg", "uid": "09eec780-fed1-488b-9321-e468e0c25343", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "max_degree", "parameter": true, "order": 9, "description": "Max polynomial degree (applies to Poly)"}}, {"pk": 238, "model": "workflows.abstractinput", "fields": {"widget": 87, "name": "depth", "short_name": "dpt", "uid": "3541b804-e8f3-42c5-b022-c0b7a51f05e1", "default": "10", "required": false, "multi": false, "parameter_type": "text", "variable": "depth", "parameter": true, "order": 9, "description": "Sets an upper bound on the proof depth to which theorem-proving proceeds."}}, {"pk": 258, "model": "workflows.abstractinput", "fields": {"widget": 89, "name": "ont4", "short_name": "ont", "uid": "0c790fc0-5f7f-4117-9b9f-dae365eb88f4", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "ont4", "parameter": false, "order": 9, "description": ""}}, {"pk": 675, "model": "workflows.abstractinput", "fields": {"widget": 298, "name": "Delimiter", "short_name": "dlt", "uid": "fd2eff8a-b2d0-4de6-9384-13ce5385e3fc", "default": ",", "required": false, "multi": false, "parameter_type": "text", "variable": "delimiter", "parameter": true, "order": 9, "description": "Define delimiter to parse the data."}}, {"pk": 685, "model": "workflows.abstractinput", "fields": {"widget": 302, "name": "Random state", "short_name": "rsd", "uid": "8e6e2d96-3457-4b23-ac93-ab90b083920f", "default": "None", "required": true, "multi": false, "parameter_type": "text", "variable": "seed", "parameter": true, "order": 9, "description": "Define a random state"}}, {"pk": 699, "model": "workflows.abstractinput", "fields": {"widget": 307, "name": "Random state", "short_name": "rsd", "uid": "31c68e34-3bff-41bb-bf77-925c6171a6f6", "default": "None", "required": true, "multi": false, "parameter_type": "text", "variable": "seed", "parameter": true, "order": 9, "description": "Define a random state"}}, {"pk": 76, "model": "workflows.abstractinput", "fields": {"widget": 40, "name": "Use cellular components ontology", "short_name": "cel", "uid": "e7d498a1-042b-4d52-b8a0-0c7941867bc5", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "useCellularComponents", "parameter": true, "order": 10, "description": "Use cellular components ontology"}}, {"pk": 79, "model": "workflows.abstractinput", "fields": {"widget": 43, "name": "Use cellular components ontology", "short_name": "cel", "uid": "0d604ef5-498d-4df4-be1a-a9465263fded", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "useCellularComponents", "parameter": true, "order": 10, "description": "Use cellular components ontology"}}, {"pk": 131, "model": "workflows.abstractinput", "fields": {"widget": 57, "name": "Use cellular components ontology", "short_name": "cel", "uid": "bf731c43-4c16-4665-ab52-1a43cd07db6e", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "useCellularComponents", "parameter": true, "order": 10, "description": "Use cellular components ontology"}}, {"pk": 173, "model": "workflows.abstractinput", "fields": {"widget": 73, "name": "Multi-terms in a sentence", "short_name": "mtn", "uid": "0343cf50-bacf-4e07-90d6-ecbeb19986d2", "default": "1", "required": false, "multi": false, "parameter_type": "text", "variable": "num_multiterms", "parameter": true, "order": 10, "description": "Multi-terms in a sentence"}}, {"pk": 215, "model": "workflows.abstractinput", "fields": {"widget": 83, "name": "data format", "short_name": "fmt", "uid": "e3ae46df-56bf-4137-97bc-a98214dd6525", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "dataFormat", "parameter": true, "order": 10, "description": "data format (tab or list)"}}, {"pk": 236, "model": "workflows.abstractinput", "fields": {"widget": 87, "name": "evalfn", "short_name": "efn", "uid": "27ed0924-8fa9-4cad-b033-c0a98db9f366", "default": "coverage", "required": false, "multi": false, "parameter_type": "select", "variable": "evalfn", "parameter": true, "order": 10, "description": "Sets the evaluation function for a search."}}, {"pk": 277, "model": "workflows.abstractinput", "fields": {"widget": 89, "name": "mapping", "short_name": "map", "uid": "e9b6fee9-ca19-4aaf-9acf-9ecb98f11f5b", "default": "", "required": false, "multi": false, "parameter_type": null, "variable": "mapping", "parameter": false, "order": 10, "description": ""}}, {"pk": 674, "model": "workflows.abstractinput", "fields": {"widget": 298, "name": "Missing values", "short_name": "mv", "uid": "f393261f-ba93-4ed5-bdfc-82f6027bb327", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "missing_vals", "parameter": true, "order": 10, "description": "Missing data values are skipped.\r\n\r\nExample: ?,"}}, {"pk": 61, "model": "workflows.abstractinput", "fields": {"widget": 40, "name": "Max reported rules", "short_name": "mrr", "uid": "30c599b6-d51b-4ec2-b49d-5724abae1e63", "default": "100", "required": false, "multi": false, "parameter_type": "text", "variable": "maxReported", "parameter": true, "order": 11, "description": "Max reported rules"}}, {"pk": 88, "model": "workflows.abstractinput", "fields": {"widget": 43, "name": "Max reported rules", "short_name": "mrr", "uid": "bdf88e4b-432c-4495-bf00-1b5e3267ce01", "default": "100", "required": false, "multi": false, "parameter_type": "text", "variable": "maxReported", "parameter": true, "order": 11, "description": "Max reported rules"}}, {"pk": 126, "model": "workflows.abstractinput", "fields": {"widget": 57, "name": "Max reported rules", "short_name": "mrr", "uid": "549e0f34-14e9-4012-9824-3f610a8531b3", "default": "100", "required": false, "multi": false, "parameter_type": "text", "variable": "maxReported", "parameter": true, "order": 11, "description": "Max reported rules"}}, {"pk": 177, "model": "workflows.abstractinput", "fields": {"widget": 73, "name": "One term should occur at the beginning of the sentence", "short_name": "tbs", "uid": "4eed193a-62b1-406f-8a6a-7d21fc02a2bd", "default": "false", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "term_beginning", "parameter": true, "order": 11, "description": "One term should occur at the beginning of the sentence"}}, {"pk": 239, "model": "workflows.abstractinput", "fields": {"widget": 87, "name": "i", "short_name": "i", "uid": "48905a20-0192-40c0-82de-2389e8fdc88e", "default": "2", "required": false, "multi": false, "parameter_type": "text", "variable": "i", "parameter": true, "order": 11, "description": "Set upper bound on layers of new variables."}}, {"pk": 249, "model": "workflows.abstractinput", "fields": {"widget": 88, "name": "subgroups", "short_name": "sg", "uid": "1c982c21-0b97-40d1-a35e-30ba16342b00", "default": "", "required": true, "multi": false, "parameter_type": "checkbox", "variable": "subgroups", "parameter": true, "order": 11, "description": "find subgroups as well"}}, {"pk": 265, "model": "workflows.abstractinput", "fields": {"widget": 89, "name": "weightGSEA", "short_name": "wei", "uid": "3e15d380-742f-4134-8093-097e053bdccb", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "weightGSEA", "parameter": true, "order": 11, "description": ""}}, {"pk": 665, "model": "workflows.abstractinput", "fields": {"widget": 298, "name": "Class mapping", "short_name": "map", "uid": "04fb15c3-7d69-43e7-a009-0eb9a3c3a33e", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "y_map", "parameter": true, "order": 11, "description": "The class mapping defines a mapping for a binary class. It is used with Logistic regression and Linear SVM.\r\n\r\nThe Logistic regression classifier uses 0 and 1 as class. If the dataset contains discrete classes  (e.g. healthy, sick), a mapping should be defined, where healthy is mapped to 1 and sick to 0. The class mapping is used only with binary target labels.\r\nExample: healthy, sick"}}, {"pk": 60, "model": "workflows.abstractinput", "fields": {"widget": 40, "name": "Use KEGG ontology", "short_name": "keg", "uid": "1d39bace-eeb6-4364-97f4-24fad14ae32c", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "useKEGG", "parameter": true, "order": 12, "description": "Use KEGG ontology"}}, {"pk": 91, "model": "workflows.abstractinput", "fields": {"widget": 43, "name": "Use KEGG ontology", "short_name": "keg", "uid": "c9504bec-4315-4272-a68e-2a050fce653d", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "useKEGG", "parameter": true, "order": 12, "description": "Use KEGG ontology"}}, {"pk": 128, "model": "workflows.abstractinput", "fields": {"widget": 57, "name": "Use KEGG ontology", "short_name": "keg", "uid": "7df06a95-70ca-4b7f-ab73-3deabc4e3462", "default": "true", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "useKEGG", "parameter": true, "order": 12, "description": "Use KEGG ontology"}}, {"pk": 243, "model": "workflows.abstractinput", "fields": {"widget": 87, "name": "language", "short_name": "lan", "uid": "9de49bde-7518-4116-8606-eccc134d1d8f", "default": "inf", "required": false, "multi": false, "parameter_type": "text", "variable": "language", "parameter": true, "order": 12, "description": "Specifies the number of occurences of a predicate symbol in any clause (inf or > 0)."}}, {"pk": 275, "model": "workflows.abstractinput", "fields": {"widget": 89, "name": "wracc_k", "short_name": "wra", "uid": "cb312cf6-2e82-4f17-8f36-8b0f8d17a8e0", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "wracc_k", "parameter": true, "order": 12, "description": ""}}, {"pk": 73, "model": "workflows.abstractinput", "fields": {"widget": 40, "name": "maximalPvalue", "short_name": "mxp", "uid": "c937aa5b-87e6-4105-bea8-20ccbd1bd488", "default": "0.05", "required": false, "multi": false, "parameter_type": "text", "variable": "maximalPvalue", "parameter": true, "order": 13, "description": "Maximal p-value"}}, {"pk": 95, "model": "workflows.abstractinput", "fields": {"widget": 43, "name": "maximalPvalue", "short_name": "mxp", "uid": "ee629b94-7897-45dc-949c-158f1cd6fab4", "default": "0.05", "required": false, "multi": false, "parameter_type": "text", "variable": "maximalPvalue", "parameter": true, "order": 13, "description": "Maximal p-value"}}, {"pk": 130, "model": "workflows.abstractinput", "fields": {"widget": 57, "name": "maximalPvalue", "short_name": "mxp", "uid": "964f5419-a0c0-4324-acd1-43320b32c638", "default": "0.05", "required": false, "multi": false, "parameter_type": "text", "variable": "maximalPvalue", "parameter": true, "order": 13, "description": "Maximal p-value"}}, {"pk": 244, "model": "workflows.abstractinput", "fields": {"widget": 87, "name": "m", "short_name": "m", "uid": "b07b2b85-bc8f-4dfc-aaf8-800b94077312", "default": "1", "required": false, "multi": false, "parameter_type": "text", "variable": "m", "parameter": true, "order": 13, "description": "Sets a value for \"m-estimate\" calculations."}}, {"pk": 273, "model": "workflows.abstractinput", "fields": {"widget": 89, "name": "maximalPvalue", "short_name": "max", "uid": "b2b31c12-b1aa-4b7f-ace7-005035b92ed7", "default": "", "required": false, "multi": false, "parameter_type": "text", "variable": "maximalPvalue", "parameter": true, "order": 13, "description": ""}}, {"pk": 72, "model": "workflows.abstractinput", "fields": {"widget": 40, "name": "Minimal set size", "short_name": "mss", "uid": "c3d26859-c452-44ea-a1fb-6bdc02d50090", "default": "20", "required": false, "multi": false, "parameter_type": "text", "variable": "minimalSetSize", "parameter": true, "order": 14, "description": "Minimal set size"}}, {"pk": 86, "model": "workflows.abstractinput", "fields": {"widget": 43, "name": "Minimal set size", "short_name": "mss", "uid": "ae0e77ed-0838-45ec-9f49-45dbcda7bd20", "default": "20", "required": false, "multi": false, "parameter_type": "text", "variable": "minimalSetSize", "parameter": true, "order": 14, "description": "Minimal set size"}}, {"pk": 122, "model": "workflows.abstractinput", "fields": {"widget": 57, "name": "Minimal set size", "short_name": "mss", "uid": "1e1141ab-efd0-47e8-9f61-39a824f79c83", "default": "20", "required": false, "multi": false, "parameter_type": "text", "variable": "minimalSetSize", "parameter": true, "order": 14, "description": "Minimal set size"}}, {"pk": 240, "model": "workflows.abstractinput", "fields": {"widget": 87, "name": "max_features", "short_name": "mxf", "uid": "4a275a37-e6bc-4b22-816d-b45e2ac791e2", "default": "inf", "required": false, "multi": false, "parameter_type": "text", "variable": "max_features", "parameter": true, "order": 14, "description": "Sets an upper bound on the maximum number of boolean features constructed by searching for good clauses (inf or > 0)."}}, {"pk": 261, "model": "workflows.abstractinput", "fields": {"widget": 89, "name": "legacy", "short_name": "leg", "uid": "15610106-cd5b-4dee-a3d1-ead67a3dc546", "default": "", "required": false, "multi": false, "parameter_type": "checkbox", "variable": "legacy", "parameter": true, "order": 14, "description": ""}}, {"pk": 75, "model": "workflows.abstractinput", "fields": {"widget": 40, "name": "Maximum number of terms", "short_name": "mnt", "uid": "da6f4408-ab85-4b47-85ef-f3f99cef1a12", "default": "3", "required": false, "multi": false, "parameter_type": "text", "variable": "maxNumTerms", "parameter": true, "order": 15, "description": "Maximum number of terms"}}, {"pk": 82, "model": "workflows.abstractinput", "fields": {"widget": 43, "name": "Maximum number of terms", "short_name": "mnt", "uid": "28a94f0b-3a02-4b6c-b076-54db4479cd98", "default": "3", "required": false, "multi": false, "parameter_type": "text", "variable": 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split.\r\n\u201cauto\u201d, then max_features=sqrt(n_features).\r\n\u201csqrt\u201d, then max_features=sqrt(n_features).\r\n\u201clog2\u201d, then max_features=log2(n_features).\r\nNone, then max_features=n_features.\r\n\r\nmax_depth : {integer} The maximum depth of the tree. \r\n"}}, {"pk": 34, "model": "workflows.abstractwidget", "fields": {"category": 5, "treeview_image": "", "name": "Decision support charts", "is_streaming": false, "uid": "7640481a-3fa7-42b0-b878-e6c1f2dc359f", "interaction_view": "", "image": "", "package": "decision_support", "static_image": "piechart.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "decision_support_charts_viewer", "streaming_visualization_view": "", "action": "decision_support_charts", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 308, "model": "workflows.abstractwidget", "fields": {"category": 55, "treeview_image": "", "name": 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{"pk": 120, "model": "workflows.abstractwidget", "fields": {"category": 19, "treeview_image": "", "name": "Hierarchical clustering", "is_streaming": false, "uid": "12b0d57d-1cbc-4e9d-8087-2dcd8ced2a27", "interaction_view": "cforange_hierarchical_clustering", "image": "", "package": "cforange", "static_image": "HierarchicalClustering_60.png", "post_interact_action": "cforange_hierarchical_clustering_finished", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "cforange_hierarchical_clustering", "wsdl_method": "", "wsdl": "", "interactive": true, "has_progress_bar": false, "order": 1, "description": "The widget computes hierarchical clustering of arbitrary types of objects from the matrix of distances between them and shows the corresponding diagram. 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"interaction_view": "", "image": "", "package": "scikitAlgorithms", "static_image": "scikit_LARS.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "scikitAlgorithms_LassoLARS", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "L1-regularized least squares linear model trained with Least Angle Regression"}}, {"pk": 119, "model": "workflows.abstractwidget", "fields": {"category": 21, "treeview_image": "", "name": "Leave One Out", "is_streaming": false, "uid": "0e9514ce-914a-4dd0-9952-9cd14877c427", "interaction_view": "", "image": "", "package": "cforange", "static_image": "leaveOneOut.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "cforange_leave_one_out", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Performs a leave-one-out experiment with the given list of learners and examples. This is equivalent to performing len(examples)-fold cross validation. Function accepts additional keyword arguments for preprocessing, storing classifiers and verbose output."}}, {"pk": 112, "model": "workflows.abstractwidget", "fields": {"category": 16, "treeview_image": "", "name": "LibSVM", "is_streaming": false, "uid": "dc1efcee-56bc-40b0-a699-b3750d4651ac", "interaction_view": "", "image": "", "package": "weka", "static_image": "WEKA_LibSVM.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "call_webservice", "wsdl_method": "LibSVM", "wsdl": "http://vihar.ijs.si:8092/Classification?wsdl", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Support Vector Machine learner."}}, {"pk": 271, "model": "workflows.abstractwidget", "fields": {"category": 44, "treeview_image": "", "name": "Lift curves", "is_streaming": false, "uid": "a81db0a6-3f8b-4d9b-ba79-a8ad2f6c2a4d", "interaction_view": "", "image": "", "package": "vipercharts", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "vipercharts_lift_curve_view", "streaming_visualization_view": "", "action": "vipercharts_lift_curve", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 202, "model": "workflows.abstractwidget", "fields": {"category": 29, "treeview_image": "", "name": "Linear Support Vector Classification", "is_streaming": false, "uid": "bab37f12-8d69-4823-a86b-13af7e1cb00d", "interaction_view": "", "image": "", "package": "scikitAlgorithms", "static_image": "scikit_svm.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "scikitAlgorithms_linearSVC", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Support Vector Machines without kernels based on liblinear\r\n\r\nC : {float} - Penalty parameter C of the error term.\r\nloss : string, \u2018l1\u2019 or \u2018l2\u2019 (default=\u2019l2\u2019) Specifies the loss function. \u2018l1\u2019 is the hinge loss (standard SVM) while \u2018l2\u2019 is the squared hinge loss.\r\npenalty : string, \u2018l1\u2019 or \u2018l2\u2019 (default=\u2019l2\u2019) Specifies the norm used in the penalization. The \u2018l2\u2019 penalty is the standard used in SVC. The \u2018l1\u2019 leads to coef_ vectors that are sparse.\r\n\r\nmulti_class: string, \u2018ovr\u2019 or \u2018crammer_singer\u2019 (default=\u2019ovr\u2019) :\r\nDetermines the multi-class strategy if y contains more than two classes. ovr trains n_classes one-vs-rest classifiers, while crammer_singer optimizes a joint objective over all classes. While crammer_singer is interesting from an theoretical perspective as it is consistent it is seldom used in practice and rarely leads to better accuracy and is more expensive to compute. 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NIPS 2006.   \r\n"}}, {"pk": 199, "model": "workflows.abstractwidget", "fields": {"category": 29, "treeview_image": "", "name": "Logistic Regression", "is_streaming": false, "uid": "acd016b6-fd34-42d2-aa2c-25a812af2cf6", "interaction_view": "", "image": "", "package": "scikitAlgorithms", "static_image": "scikit_LogisticRegression.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "scikitAlgorithms_logiscticRegression", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "penalty : {string} Used to specify the norm used in the penalization.\r\n\u2018l1\u2019 or \u2018l2\u2019\r\n\r\nC : {float} \r\nInverse of regularization strength; must be a positive float. 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"}}, {"pk": 114, "model": "workflows.abstractwidget", "fields": {"category": 16, "treeview_image": "", "name": "Multilayer Perceptron", "is_streaming": false, "uid": "fa4f24ac-1055-408a-852f-1ce4d90ef3ce", "interaction_view": "", "image": "", "package": "weka", "static_image": "WEKA_MultilPerceptron.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "call_webservice", "wsdl_method": "Multilayer_Perceptron", "wsdl": "http://vihar.ijs.si:8092/Classification?wsdl", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 178, "model": "workflows.abstractwidget", "fields": {"category": 25, "treeview_image": "", "name": "MySQL Connect", "is_streaming": false, "uid": "41978deb-c245-4e1f-95a2-ceadcfe6898a", "interaction_view": "", "image": "", "package": "mysql", "static_image": "mysql.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "mysql_connect", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 100, "model": "workflows.abstractwidget", "fields": {"category": 16, "treeview_image": "", "name": "Naive Bayes", "is_streaming": false, "uid": "8283f38a-33dc-4d0d-812d-1c58c7209469", "interaction_view": "", "image": "", "package": "weka", "static_image": "WEKA_naiveBayes.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "call_webservice", "wsdl_method": "Naive_Bayes", "wsdl": "http://vihar.ijs.si:8092/Classification?wsdl", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 301, "model": "workflows.abstractwidget", "fields": {"category": 52, "treeview_image": "", "name": "Naive Bayes", "is_streaming": false, "uid": "477a2f37-5015-4a46-a243-08c8e84256b7", "interaction_view": "", "image": "", "package": "big_data", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "naivebayes_fit", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Naive Bayes with MapReduce\r\n\r\nAlgorithm calculates multinomial distribution for discrete features and Gaussian distribution for numerical features. 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"action": "string_to_file", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 138, "model": "workflows.abstractwidget", "fields": {"category": 8, "treeview_image": "", "name": "Orange Data Table to TAB File", "is_streaming": false, "uid": "6f475ead-0c0e-4b77-bc1a-ccfa7614962c", "interaction_view": "", "image": "", "package": "cforange", "static_image": "ODT-to-TAB.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "odt_to_tab", "streaming_visualization_view": "", "action": "string_to_file", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 174, "model": "workflows.abstractwidget", "fields": {"category": 24, "treeview_image": "treeview/Bar-chart-icon.png", "name": "Performance Chart", "is_streaming": false, "uid": "4c667e7a-82fe-4dc3-8f70-48fc261e0eee", "interaction_view": "", "image": 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{"category": 6, "treeview_image": "", "name": "Prepare Results for PR Visualization", "is_streaming": false, "uid": "b16da039-f997-4d78-baa0-26d5ad8661eb", "interaction_view": "", "image": "", "package": "cforange", "static_image": "PR.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "cforange_prepare_results", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 98, "model": "workflows.abstractwidget", "fields": {"category": 14, "treeview_image": "", "name": "Print Model", "is_streaming": false, "uid": "5ac9aced-9520-4ea4-ac0d-bc58c8be2aef", "interaction_view": "", "image": "", "package": "weka", "static_image": "WEKA_printModel.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "call_webservice", "wsdl_method": "print_model", "wsdl": "http://vihar.ijs.si:8092/Utilities?wsdl", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 108, "model": "workflows.abstractwidget", "fields": {"category": 14, "treeview_image": "", "name": "Print Tree", "is_streaming": false, "uid": "bc3756b6-7f76-48ed-ae71-8bdae8870b23", "interaction_view": "", "image": "", "package": "weka", "static_image": "WEKA_printTree.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "call_webservice", "wsdl_method": "print_tree", "wsdl": "http://vihar.ijs.si:8092/Utilities?wsdl", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 156, "model": "workflows.abstractwidget", "fields": {"category": 21, "treeview_image": "", "name": "Proportion Test", "is_streaming": false, "uid": "c605a0f4-a3b0-4394-8410-9da8854416a2", "interaction_view": "", "image": "", "package": "cforange", "static_image": "proportionTest.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "cforange_proportion_test", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Splits the data with a number of examples in the learning and the rest in the testing set. The test is repeated for a given number of times (default 10). Division is stratified by default. Function also accepts keyword arguments for randomization and storing classifiers."}}, {"pk": 123, "model": "workflows.abstractwidget", "fields": {"category": 23, "treeview_image": "", "name": "R-squared", "is_streaming": false, "uid": "2299e615-4d72-4db7-9b32-3566b903c749", "interaction_view": "", "image": "", "package": "cforange", "static_image": "R2.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "cforange_R2", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "One of the several alternative measures to be used to evaluate the success of numeric prediction."}}, {"pk": 99, "model": "workflows.abstractwidget", "fields": {"category": 16, "treeview_image": "", "name": "REP Tree", "is_streaming": false, "uid": "77f625ba-46fd-4c7c-bcc1-ab279682a02c", "interaction_view": "", "image": "", "package": "weka", "static_image": "WEKA_REPTree.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "call_webservice", "wsdl_method": "REPTree", "wsdl": "http://vihar.ijs.si:8092/Classification?wsdl", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 267, "model": "workflows.abstractwidget", "fields": {"category": 42, "treeview_image": "", "name": "ROC space", "is_streaming": false, "uid": "8c94168c-9260-453a-bcbd-96bee7bc1236", "interaction_view": "", "image": "", "package": "vipercharts", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "vipercharts_roc_space_view", "streaming_visualization_view": "", "action": "vipercharts_roc_space", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 88, "model": "workflows.abstractwidget", "fields": {"category": 12, "treeview_image": "", "name": "RSD", "is_streaming": false, "uid": "dabcb4ed-ae86-4f3e-8d3e-bb0306ff11f8", "interaction_view": "", "image": "", "package": "ilp", "static_image": "ilp.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "ilp_rsd", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Relational subgroup discovery by Zelezny et al."}}, {"pk": 214, "model": "workflows.abstractwidget", "fields": {"category": 32, "treeview_image": "", "name": "RSS Reader", "is_streaming": true, "uid": "723e4654-abf4-4c9f-920f-08915c4d7a72", "interaction_view": "", "image": "", "package": "streaming", "static_image": "rss.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "streaming_rss_reader", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 90, "model": "workflows.abstractwidget", "fields": {"category": 16, "treeview_image": "treeview/Toolbar_-_Loop.png", "name": "Random Tree", "is_streaming": false, "uid": "0adcbc66-4b1a-475b-b82f-42682050c8f4", "interaction_view": "", "image": "images/Toolbar_-_Loop.png", "package": "weka", "static_image": "WEKA_RandomTree.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "call_webservice", "wsdl_method": "RandomTree", "wsdl": "http://vihar.ijs.si:8092/Classification?wsdl", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 302, "model": "workflows.abstractwidget", "fields": {"category": 55, "treeview_image": "", "name": "Random forest", "is_streaming": false, "uid": "4f2ce923-62e6-4be1-a394-72ac52988386", "interaction_view": "", "image": "", "package": "big_data", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "rf_fit", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Random forest with MapReduce\r\n\r\nFit phase\r\nRandom forest algorithm builds multiple decision trees with a bootstrap method on a subset of data. \r\nIn each tree node, it estimates sqrt(num. of attributes)+1 randomly selected attributes (without replacement).\r\nAll decision trees are merged in large ensemble.  \r\n\r\nPredict phase\r\nAlgorithm queries as many trees as needed for reliable prediction.\r\nFirstly, it randomly chooses without replacement 15 trees. If all trees vote for the same class, it outputs prediction. If there are multiple classes predicted, it chooses 15 trees again. Algorithm calculates difference in probability between most and second most probable prediction. If difference is greater than parameter diff, it outputs prediction. If a test sample is hard to predict (difference is never higher than diff), it queries whole ensemble to make a prediction.\r\n\r\nReference\r\nSimilar algorithm is proposed in: Justin D Basilico, M Arthur Munson, Tamara G Kolda, Kevin R Dixon, and W Philip Kegelmeyer. Comet: A recipe for learning and using large ensembles on massive data. \r\n"}}, {"pk": 106, "model": "workflows.abstractwidget", "fields": {"category": 16, "treeview_image": "treeview/120px-Gears_icon.png", "name": "RandomForest", "is_streaming": false, "uid": "a86057ba-aa1f-40fe-a548-e6c3259b7a6e", "interaction_view": "", "image": "images/120px-Gears_icon.png", "package": "weka", "static_image": "WEKA_RandomForest.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "call_webservice", "wsdl_method": "RandomForest", "wsdl": "http://vihar.ijs.si:8092/Classification?wsdl", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Random Forest learner."}}, {"pk": 60, "model": "workflows.abstractwidget", "fields": {"category": 7, "treeview_image": "", "name": "Rank plotter", "is_streaming": false, "uid": "ca7934af-8583-47ab-8c68-ca6e45405bcc", "interaction_view": "", "image": "", "package": "segmine", "static_image": "RankPlotter.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "segmine_rank_plotter", "streaming_visualization_view": "", "action": "segmine_rank_plotter", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 20, "model": "workflows.abstractwidget", "fields": {"category": 1, "treeview_image": "", "name": "Ravel list", "is_streaming": false, "uid": "ac754eed-37a4-48bc-b837-2f3db3f8f547", "interaction_view": "", "image": "", "package": "base", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "base_ravel_list", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Ravels and removes empty sublists from the input list. Useful in for loops."}}, {"pk": 36, "model": "workflows.abstractwidget", "fields": {"category": 7, "treeview_image": "", "name": "Read microarray data from file", "is_streaming": false, "uid": "01aad79e-9991-412c-b619-cb87a956b65a", "interaction_view": "", "image": "", "package": "segmine", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "segmine_read_microarray_data", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Reads a csv of gene expression data in SegMine specific format into an Orange data table."}}, {"pk": 70, "model": "workflows.abstractwidget", "fields": {"category": 9, "treeview_image": "", "name": "RelSets", "is_streaming": false, "uid": "e7f36086-20d2-4b8f-b4e1-4eec195e786b", "interaction_view": "", "image": "", "package": "subgroup_discovery", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "call_webservice", "wsdl_method": "relSets", "wsdl": "http://zulu.ijs.si:8085/RS_services?wsdl", "interactive": false, "has_progress_bar": false, "order": 1, "description": "The RelSets algorithm proposed by Garriga et al. (2008):\r\nhttp://jmlr.org/papers/v9/garriga08a.html\r\n\r\nImplemented as a web-service by Podpecan and Kralj:\r\nhttp://kt.ijs.si/petra_kralj/RelSets/"}}, {"pk": 117, "model": "workflows.abstractwidget", "fields": {"category": 23, "treeview_image": "", "name": "Relative Squared Error", "is_streaming": false, "uid": "0d32c3a7-1f94-4414-92f0-bb81a9152636", "interaction_view": "", "image": "", "package": "cforange", "static_image": "RSE.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "cforange_RSE", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "One of the several alternative measures to be used to evaluate the success of numeric prediction."}}, {"pk": 208, "model": "workflows.abstractwidget", "fields": {"category": 32, "treeview_image": "", "name": "Remove words from tweets", "is_streaming": false, "uid": "258e97c6-e44d-41a3-97c0-689de94f3049", "interaction_view": "", "image": "", "package": "streaming", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "streaming_remove_words_from_tweets", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 53, "model": "workflows.abstractwidget", "fields": {"category": 7, "treeview_image": "", "name": "Resolve STU gene names", "is_streaming": false, "uid": "a3575a7a-770e-4200-b4b4-97c2d993c1b5", "interaction_view": "", "image": "", "package": "segmine", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "resolve_gene_names_STU", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Maps known probe STU gene names into GoMapMan/rep names"}}, {"pk": 47, "model": "workflows.abstractwidget", "fields": {"category": 7, "treeview_image": "", "name": "Resolve gene synonyms", "is_streaming": false, "uid": "533f57dc-a21d-4e02-9405-023620fcc39b", "interaction_view": "", "image": "", "package": "segmine", "static_image": "genesynonyms.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "segmine_resolve_gene_synonyms", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 197, "model": "workflows.abstractwidget", "fields": {"category": 28, "treeview_image": "", "name": "Ridge", "is_streaming": false, "uid": "5f1d2eba-123f-41f4-ac54-118c6cf036ff", "interaction_view": "", "image": "", "package": "scikitAlgorithms", "static_image": "scikit_RDG.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "scikitAlgorithms_Ridge", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "L2-regularized least squares linear model"}}, {"pk": 163, "model": "workflows.abstractwidget", "fields": {"category": 23, "treeview_image": "", "name": "Root Mean-squared Error", "is_streaming": false, "uid": "dc66f264-14a6-491b-9c39-36bded8f95d0", "interaction_view": "", "image": "", "package": "cforange", "static_image": "MSE2.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "cforange_RMSE", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "One of the several alternative measures to be used to evaluate the success of numeric prediction."}}, {"pk": 157, "model": "workflows.abstractwidget", "fields": {"category": 23, "treeview_image": "", "name": "Root Relative Squared Error", "is_streaming": false, "uid": "c9ecd12e-eaff-41b6-b104-dff7fb60b124", "interaction_view": "", "image": "", "package": "cforange", "static_image": "RSE2.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "cforange_RRSE", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "One of the several alternative measures to be used to evaluate the success of numeric prediction."}}, {"pk": 83, "model": "workflows.abstractwidget", "fields": {"category": 12, "treeview_image": "", "name": "SDM-Aleph", "is_streaming": false, "uid": "14c7c1f8-d9ee-43da-9c7d-c979d3533fe7", "interaction_view": "", "image": "", "package": "ilp", "static_image": "ws.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "ilp_sdmaleph", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "    SDM-Aleph web service.\r\n    \r\n    Inputs:\r\n        - examples: str, a .tab dataset or a list of pairs\r\n        - mapping : str, a mapping between examples and ontological terms,\r\n        - ontologies : a list of {'ontology' : str} dicts\r\n        - relations : a list of {'relation' : str} dicts\r\n        - posClassVal : str, if the data is class-labeled, this is the target class,\r\n        - cutoff : int, if the data is ranked, this is the cutoff value for splitting it into two classes,\r\n        - minPos : int >= 1, minimum number of true positives per rule\r\n        - noise : int > 0, false positives allowed per rule\r\n        - clauseLen : int >= 1, number of predicates per clause,\r\n        - dataFormat : str, legal values are 'tab' or 'list'\r\n    Output:\r\n        - str, the induced theory.\r\n    \r\n    @author: Anze Vavpetic, 2011 <anze.vavpetic@ijs.si>"}}, {"pk": 89, "model": "workflows.abstractwidget", "fields": {"category": 12, "treeview_image": "", "name": "SDM-SEGS", "is_streaming": false, "uid": "fd68201e-c2ce-45ad-85ea-41e7171f69bd", "interaction_view": "", "image": "", "package": "ilp", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "call_webservice", "wsdl_method": "sdmsegs", "wsdl": "http://vihar.ijs.si:8096/", "interactive": false, "has_progress_bar": false, "order": 1, "description": "\t\t\t\t\r\n    SDM-SEGS web service.\r\n    \r\n    Inputs:\r\n        - inputData: str, a .tab dataset or a (pythonish) list of pairs\r\n        - interactions: str, list of interacting examples,\r\n        - mapping : str, a mapping between examples and ontological terms,\r\n        - ont1-4 : str, ontologies in OWL (legacy=false), or in SEGS's format (legacy=true)\r\n        - generalTerms : str, terms that are too general (each in new line),\r\n        - legacy : bool, turns on SEGS mode,\r\n        - posClassVal : str, if the data is class-labeled, this is the target class,\r\n        - cutoff : int, if the data is ranked, this is the cutoff value for splitting it into two classes,\r\n        - wracc_k : int, number of times an example can be covered when selecting with WRAcc,\r\n        - minimalSetSize : int, minimum number of covered examples,\r\n        - maxNumTerms : int, maximum number of conjunctions in one rule,\r\n        - maxReported : int, number of returned rules,\r\n        - maximalPvalue : float, maximum p-value of a returned rule,\r\n        - weightFisher, weightGSEA, weightPAGE : float, weights for corresponding score functions; makes sense only if legacy = false,\r\n        - dataFormat : str, legal values are 'tab' or 'list'\r\n    Output:\r\n        - json dictionary encoding the discovered rules.\r\n        \r\n    Note: See http://kt.ijs.si/software/SEGS/ for legacy format specification.\r\n    \r\n    @author: Anze Vavpetic, 2011 <anze.vavpetic@ijs.si>\r\n    \r\n\t\t\t"}}, {"pk": 86, "model": "workflows.abstractwidget", "fields": {"category": 12, "treeview_image": "", "name": "SDM-SEGS Rule Viewer", "is_streaming": false, "uid": "792b7437-a9b5-4fca-8b21-f9939e9ff8e7", "interaction_view": "", "image": "", "package": "ilp", "static_image": "ilp.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "ilp_sdmsegs_rule_viewer", "streaming_visualization_view": "", "action": "ilp_sdmsegs_rule_viewer", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 57, "model": "workflows.abstractwidget", "fields": {"category": 7, "treeview_image": "", "name": "SEGS", "is_streaming": false, "uid": "b947b5fc-e992-43c9-9c99-7f47f4b0537c", "interaction_view": "", "image": "", "package": "segmine", "static_image": "SEGS_HMR.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "segmine_segs", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": true, "order": 1, "description": ""}}, {"pk": 43, "model": "workflows.abstractwidget", "fields": {"category": 7, "treeview_image": "", "name": "SEGS ATH", "is_streaming": false, "uid": "32045302-43ae-4881-9414-d04fe844843e", "interaction_view": "", "image": "", "package": "segmine", "static_image": "SEGS_HMR.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "segmine_segs_ath", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": true, "order": 1, "description": ""}}, {"pk": 39, "model": "workflows.abstractwidget", "fields": {"category": 7, "treeview_image": "", "name": "SEGS Rule browser", "is_streaming": false, "uid": "1118c133-0113-4df8-b240-8690c4b62e07", "interaction_view": "segmine_rule_browser", "image": "", "package": "segmine", "static_image": "RuleBrowser.png", "post_interact_action": "segmine_rule_browser_finished", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "segmine_rule_browser", "wsdl_method": "", "wsdl": "", "interactive": true, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 40, "model": "workflows.abstractwidget", "fields": {"category": 7, "treeview_image": "", "name": "SEGS STU", "is_streaming": false, "uid": "2bc9b86c-5c99-4ac8-afbc-d20fd34c3ca1", "interaction_view": "", "image": "", "package": "segmine", "static_image": "SEGS_HMR.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "segmine_segs_stu", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": true, "order": 1, "description": ""}}, {"pk": 51, "model": "workflows.abstractwidget", "fields": {"category": 7, "treeview_image": "", "name": "SEGS rules as Orange table", "is_streaming": false, "uid": "9ab3236a-efc3-480d-accf-7877a4e7f4e4", "interaction_view": "", "image": "", "package": "segmine", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "segmine_rules_as_table", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Transform SEGS rules into an Orange ExampleTable. Useful for e.g., clustering."}}, {"pk": 206, "model": "workflows.abstractwidget", "fields": {"category": 28, "treeview_image": "", "name": "SGD Regressor", "is_streaming": false, "uid": "fb5ccfaf-d587-4077-b69e-dc32a782ce32", "interaction_view": "", "image": "", "package": "scikitAlgorithms", "static_image": "scikit_SGD.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "scikitAlgorithms_SGDRegressor", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "L1+L2-regularized least squares linear model trained using Stochastic Gradient Descent"}}, {"pk": 104, "model": "workflows.abstractwidget", "fields": {"category": 16, "treeview_image": "", "name": "SMO", "is_streaming": false, "uid": "9fa88a17-5a6a-4173-88bf-8458dc24baea", "interaction_view": "", "image": "", "package": "weka", "static_image": "WEKA_SMO.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "call_webservice", "wsdl_method": "SMO", "wsdl": "http://vihar.ijs.si:8092/Classification?wsdl", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 188, "model": "workflows.abstractwidget", "fields": {"category": 31, "treeview_image": "", "name": "SVM to Scikit Dataset", "is_streaming": false, "uid": "125b73c7-d009-4198-8fb8-328c826b6c29", "interaction_view": "", "image": "", "package": "scikitAlgorithms", "static_image": "table.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "scikitAlgorithms_SVMtoScikitDataset", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 261, "model": "workflows.abstractwidget", "fields": {"category": 40, "treeview_image": "treeview/SF-filter_1.png", "name": "Saturation Filter", "is_streaming": false, "uid": "babfecd3-5b19-42b0-a8a5-438826ec7ff8", "interaction_view": "", "image": "images/SF-filter_1.png", "package": "noise", "static_image": "SF-filter_1.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "saturation_filter", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": true, "order": 1, "description": ""}}, {"pk": 190, "model": "workflows.abstractwidget", "fields": {"category": 31, "treeview_image": "", "name": "Scikit-Dataset to CSV", "is_streaming": false, "uid": "1bc483d6-4d6c-435f-9fc0-ad3716fe390b", "interaction_view": "", "image": "", "package": "scikitAlgorithms", "static_image": "SDT-to-CSV.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "scikitAlgorithms_scikitDatasetToCSV", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Transforms scikit dataset to CSV"}}, {"pk": 160, "model": "workflows.abstractwidget", "fields": {"category": 20, "treeview_image": "", "name": "Score estimation (Relief)", "is_streaming": false, "uid": "d7f0e9b0-aa2a-4cdb-b4a8-cfb3b0bafa43", "interaction_view": "", "image": "", "package": "cforange", "static_image": "SE.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "cforange_score_estimation", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Assesses features\u2019 ability to distinguish between very similar instances from different classes. This scoring method was first developed by Kira and Rendell and then improved by Kononenko."}}, {"pk": 294, "model": "workflows.abstractwidget", "fields": {"category": 50, "treeview_image": "", "name": "Search criteria", "is_streaming": false, "uid": "5b6ead2a-2b78-4c97-ba65-d4c6eadaf028", "interaction_view": "hbp_construct_query", "image": "", "package": "hbp", "static_image": "", "post_interact_action": "hbp_search_criteria_post", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "hbp_search_criteria", "wsdl_method": "", "wsdl": "", "interactive": true, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 144, "model": "workflows.abstractwidget", "fields": {"category": 8, "treeview_image": "treeview/Orange-SelectAttributes_60.png", "name": "Select Attributes", "is_streaming": false, "uid": "7b3455ff-5b2a-4c51-aa09-38dab4dfc2dc", "interaction_view": "select_attrs", "image": "images/Orange-SelectAttributes_60.png", "package": "cforange", "static_image": "selectattributes.png", "post_interact_action": "select_attrs_post", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "select_attrs", "wsdl_method": "", "wsdl": "", "interactive": true, "has_progress_bar": false, "order": 1, "description": "Select Attributes widget is used to manually compose your data domain, that is, to decide which attributes will be used and how. Orange distinguishes between ordinary attributes, an (optional) class attributes and meta attributes."}}, {"pk": 134, "model": "workflows.abstractwidget", "fields": {"category": 20, "treeview_image": "", "name": "Select Attributes Above Threshold", "is_streaming": false, "uid": "660c49cb-21ca-4e06-97ca-893946340b7f", "interaction_view": "", "image": "", "package": "cforange", "static_image": "selectAttrsAboveThreshold.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "cforange_atts_above_thresh", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Constructs and returns a new data set that includes a class and attributes from the list returned by function attMeasure that have the score above or equal to a specified threshold. data is used to pass an original data set. Parameter threshold is optional and defaults to 0.0."}}, {"pk": 50, "model": "workflows.abstractwidget", "fields": {"category": 7, "treeview_image": "", "name": "Select Biomine database", "is_streaming": false, "uid": "91b39cdf-e6b2-4b4f-b5c9-38ecf2ba01bf", "interaction_view": "segmine_selectBMdatabase", "image": "", "package": "segmine", "static_image": "", "post_interact_action": "segmine_selectBMdatabase_finished", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "segmine_selectBMdatabase", "wsdl_method": "", "wsdl": "", "interactive": true, "has_progress_bar": false, "order": 1, "description": "Calls the API of the new Biomine service to get the list of available databases."}}, {"pk": 122, "model": "workflows.abstractwidget", "fields": {"category": 8, "treeview_image": "treeview/orange-SelectData.png", "name": "Select Data", "is_streaming": false, "uid": "2039c5fe-48a1-426c-b418-f0a16fdf1b18", "interaction_view": "select_data", "image": "images/orange-SelectData.png", "package": "cforange", "static_image": "orange-SelectData.png", "post_interact_action": "select_data_post", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "select_data", "wsdl_method": "", "wsdl": "", "interactive": true, "has_progress_bar": false, "order": 1, "description": "This widget allows the user to select a subset of the data from the input data set based on the condition defined over a set of data\u2019s attributes. Data instances that match the selection rule are placed on the output channel."}}, {"pk": 135, "model": "workflows.abstractwidget", "fields": {"category": 20, "treeview_image": "", "name": "Select best N attributes", "is_streaming": false, "uid": "68ce4c2e-baf7-4a2e-843b-3b5622c20448", "interaction_view": "", "image": "", "package": "cforange", "static_image": "bestN.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "cforange_best_natts", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Constructs and returns a new data set that includes a class and only N best attributes from a list scores. data is used to pass an original data set."}}, {"pk": 38, "model": "workflows.abstractwidget", "fields": {"category": 7, "treeview_image": "", "name": "Select hierarchical cluster", "is_streaming": false, "uid": "0462eba5-248e-43be-a40d-0ec96530d09b", "interaction_view": "segmine_hclustering", "image": "", "package": "segmine", "static_image": "", "post_interact_action": "segmine_hclustering_finished", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "segmine_hclustering", "wsdl_method": "", "wsdl": "", "interactive": true, "has_progress_bar": false, "order": 1, "description": "A non-interactive variant of Hierarchical clustering for SegMine."}}, {"pk": 280, "model": "workflows.abstractwidget", "fields": {"category": 48, "treeview_image": "", "name": "Semantic role labeling", "is_streaming": false, "uid": "3fa29425-16dc-4c11-a51c-323da6dd30c6", "interaction_view": "", "image": "", "package": "MUSE", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "MUSE_semantic_role_labeling", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Calls the semantic role labeling service"}}, {"pk": 286, "model": "workflows.abstractwidget", "fields": {"category": 48, "treeview_image": "", "name": "Semantic role labeling (Tuk specific)", "is_streaming": false, "uid": "9c56c636-8782-4d43-96f1-9c7778e660f1", "interaction_view": "", "image": "", "package": "MUSE", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "MUSE_semantic_role_labeling_tuk", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Calls the semantic role labeling service"}}, {"pk": 35, "model": "workflows.abstractwidget", "fields": {"category": 5, "treeview_image": "", "name": "Sensitivity analysis", "is_streaming": false, "uid": "917749ce-0308-499b-be85-c987285f90db", "interaction_view": "", "image": "", "package": "decision_support", "static_image": "sensitivity.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "decision_support_sensitivity_analysis_viewer", "streaming_visualization_view": "", "action": "decision_support_sensitivity_analysis", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 76, "model": "workflows.abstractwidget", "fields": {"category": 11, "treeview_image": "treeview/nlp_1.png", "name": "Sentence viewer", "is_streaming": false, "uid": "94485ea5-f1d6-46ae-abaf-fd78988692fd", "interaction_view": "", "image": "images/nlp_7.png", "package": "nlp", "static_image": "nlp.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "definition_sentences_viewer", "streaming_visualization_view": "", "action": "definition_sentences", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 222, "model": "workflows.abstractwidget", "fields": {"category": 33, "treeview_image": "", "name": "Sentiment graph", "is_streaming": true, "uid": "c4dc0648-79b0-49e8-b670-aef1f511050d", "interaction_view": "", "image": "", "package": "streaming", "static_image": "graph.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "streaming_sentiment_graph", "action": "streaming_sentiment_graph", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 215, "model": "workflows.abstractwidget", "fields": {"category": 32, "treeview_image": "", "name": "Simulate stream from Gamasystem csv", "is_streaming": true, "uid": "7a72dcc4-53a2-4a45-96e6-31b0c2e01e32", "interaction_view": "", "image": "", "package": "streaming", "static_image": "twitter.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "streaming_simulate_stream_from_csv", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Simulates a stream from gama system's csv export"}}, {"pk": 219, "model": "workflows.abstractwidget", "fields": {"category": 32, "treeview_image": "", "name": "Simulate stream from text file", "is_streaming": true, "uid": "9a20da2e-0903-4332-8938-63b15d370657", "interaction_view": "", "image": "", "package": "streaming", "static_image": "twitter.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "streaming_simulate_stream_from_text_file", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 221, "model": "workflows.abstractwidget", "fields": {"category": 32, "treeview_image": "", "name": "Sliding Window", "is_streaming": true, "uid": "b21b4e13-8d15-4584-ad17-03405a79b020", "interaction_view": "", "image": "", "package": "streaming", "static_image": "sliding-window.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "streaming_sliding_window", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 148, "model": "workflows.abstractwidget", "fields": {"category": 8, "treeview_image": "", "name": "Split dataset", "is_streaming": false, "uid": "af4010a8-836c-41c7-adf6-50118295cf8e", "interaction_view": "", "image": "", "package": "cforange", "static_image": "split_dataset.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "cforange_split_dataset", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Splits a dataset to a train and test dataset."}}, {"pk": 209, "model": "workflows.abstractwidget", "fields": {"category": 32, "treeview_image": "", "name": "Split positive and negative tweets", "is_streaming": false, "uid": "2786eaa2-3505-4d44-9962-23df9f23c072", "interaction_view": "", "image": "", "package": "streaming", "static_image": "split.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "streaming_split_pos_neg", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 224, "model": "workflows.abstractwidget", "fields": {"category": 33, "treeview_image": "", "name": "Streaming triplet graph", "is_streaming": true, "uid": "cf3f6218-1b21-4864-9ee1-c22069abe03d", "interaction_view": "", "image": "", "package": "streaming", "static_image": "BiomineVisualizer.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "streaming_triplet_graph_visualization", "action": "streaming_triplet_graph", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 285, "model": "workflows.abstractwidget", "fields": {"category": 47, "treeview_image": "", "name": "String to statically hosted file", "is_streaming": false, "uid": "6f800e52-4d42-44aa-a981-ef554a29fb3a", "interaction_view": "MUSE_string_to_file", "image": "", "package": "MUSE", "static_image": "", "post_interact_action": "MUSE_string_to_file_finished", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "MUSE_string_to_file", "wsdl_method": "", "wsdl": "", "interactive": true, "has_progress_bar": false, "order": 1, "description": "Creates a statically served file from the given (text) content."}}, {"pk": 295, "model": "workflows.abstractwidget", "fields": {"category": 50, "treeview_image": "", "name": "Submit search criteria", "is_streaming": false, "uid": "c2c888f0-5197-46ea-8ff6-c663b031b15e", "interaction_view": "", "image": "", "package": "hbp", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "hbp_submit_search_criteria", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 216, "model": "workflows.abstractwidget", "fields": {"category": 32, "treeview_image": "", "name": "Summarize news article", "is_streaming": true, "uid": "90c0715f-36e0-4e06-a2ef-7fb88bf95943", "interaction_view": "", "image": "", "package": "streaming", "static_image": "summary.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "streaming_summarize_url", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Summarizes a news article retrieved by URL."}}, {"pk": 204, "model": "workflows.abstractwidget", "fields": {"category": 28, "treeview_image": "", "name": "Support Vector Regression", "is_streaming": false, "uid": "e9285c89-bac7-41dc-aa54-1a3ed4e94b68", "interaction_view": "", "image": "", "package": "scikitAlgorithms", "static_image": "scikit_svm.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "scikitAlgorithms_SVR", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Non-linear regression using Support Vector Machines (wrapper for libsvm)"}}, {"pk": 282, "model": "workflows.abstractwidget", "fields": {"category": 48, "treeview_image": "", "name": "Syntactic and semantic processing", "is_streaming": false, "uid": "5e5aa91e-090a-43c9-97c6-6064380b09eb", "interaction_view": "", "image": "", "package": "MUSE", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "MUSE_annotate", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Calls the LIIR NLP annotation (TERENCE NLP service)"}}, {"pk": 48, "model": "workflows.abstractwidget", "fields": {"category": 7, "treeview_image": "", "name": "T-test gene filter", "is_streaming": false, "uid": "6593a40f-1280-4d20-b399-7d182ebcdbf3", "interaction_view": "segmine_ttest_gene_filter", "image": "", "package": "segmine", "static_image": "ttest.png", "post_interact_action": "segmine_ttest_gene_filter_finished", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "segmine_ttest_gene_filter", "wsdl_method": "", "wsdl": "", "interactive": true, "has_progress_bar": false, "order": 1, "description": "Filters the genes according to t-test p-value threshold."}}, {"pk": 131, "model": "workflows.abstractwidget", "fields": {"category": 8, "treeview_image": "", "name": "Table Viewer", "is_streaming": false, "uid": "5becb9ab-93a8-4811-aa37-66ca85a7c0f3", "interaction_view": "", "image": "", "package": "cforange", "static_image": "table_viewer.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "table_viewer", "streaming_visualization_view": "", "action": "table_viewer", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Widget presents Orange Data Table in a spreadsheet format. Widget supports sorting by attribute values (click on the attribute name in the header row)."}}, {"pk": 63, "model": "workflows.abstractwidget", "fields": {"category": 8, "treeview_image": "", "name": "Table from sets of examples", "is_streaming": false, "uid": "13af5c58-1384-417e-9cc6-11e1853c19eb", "interaction_view": "table_from_sets", "image": "", "package": "subgroup_discovery", "static_image": "tablefromsets.png", "post_interact_action": "table_from_sets_finished", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "table_from_sets", "wsdl_method": "", "wsdl": "", "interactive": true, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 77, "model": "workflows.abstractwidget", "fields": {"category": 10, "treeview_image": "treeview/nlp_2.png", "name": "Term candidates viewer", "is_streaming": false, "uid": "af5ee96e-7307-46f9-8d8c-55cb7c36d111", "interaction_view": "", "image": "images/nlp_8.png", "package": "nlp", "static_image": "nlp.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "term_candidate_viewer", "streaming_visualization_view": "", "action": "term_candidates", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 75, "model": "workflows.abstractwidget", "fields": {"category": 10, "treeview_image": "", "name": "Term extraction", "is_streaming": false, "uid": "8a8f2aee-dc2e-4e1e-85d5-c977dc5c2867", "interaction_view": "", "image": "", "package": "nlp", "static_image": "nlp.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "nlp_term_extraction", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Term extraction from totrtale annotations."}}, {"pk": 228, "model": "workflows.abstractwidget", "fields": {"category": 32, "treeview_image": "", "name": "Text Sentiment Analysis", "is_streaming": true, "uid": "f54ed3e2-280e-48cf-b1f3-7e8fcfa2b94a", "interaction_view": "", "image": "", "package": "streaming", "static_image": "sentiment.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "streaming_sentiment_analysis", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 82, "model": "workflows.abstractwidget", "fields": {"category": 10, "treeview_image": "", "name": "ToTrTaLe", "is_streaming": false, "uid": "e4f7d601-4ec6-44e3-8342-cdca9d813b58", "interaction_view": "", "image": "", "package": "nlp", "static_image": "nlp.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "nlp_totrtale", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "A tool developed to process historical (Slovene) text, which annotates words in a TEI encoded corpus with their modern-day equivalents, morphosyntactic tags and lemmas. Such a tool is useful for developing historical corpora of highly-inflecting languages, enabling full text search in digital libraries of historical texts, for modernising such texts for today's readers and making it simpler to correct OCR transcriptions."}}, {"pk": 72, "model": "workflows.abstractwidget", "fields": {"category": 10, "treeview_image": "", "name": "ToTrTaLe2", "is_streaming": false, "uid": "4eec620e-f919-47d5-99f9-846ada308ac2", "interaction_view": "", "image": "", "package": "nlp", "static_image": "nlp.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "nlp_totrtale2", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "A tool developed to process historical (Slovene) text, which annotates words in a TEI encoded corpus with their modern-day equivalents, morphosyntactic tags and lemmas. Such a tool is useful for developing historical corpora of highly-inflecting languages, enabling full text search in digital libraries of historical texts, for modernising such texts for today's readers and making it simpler to correct OCR transcriptions."}}, {"pk": 126, "model": "workflows.abstractwidget", "fields": {"category": 8, "treeview_image": "", "name": "Tree Visualization", "is_streaming": false, "uid": "39e85968-5f6e-4ac7-802b-5260b406e123", "interaction_view": "", "image": "", "package": "cforange", "static_image": "TreeVisualization.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "tree_visualization", "streaming_visualization_view": "", "action": "tree_visualization", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Used to visually represent classification trees."}}, {"pk": 84, "model": "workflows.abstractwidget", "fields": {"category": 12, "treeview_image": "", "name": "TreeLiker", "is_streaming": false, "uid": "5b768023-a9df-4487-abf7-29844738cf7c", "interaction_view": "", "image": "", "package": "ilp", "static_image": "ilp.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "ilp_treeliker", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 225, "model": "workflows.abstractwidget", "fields": {"category": 32, "treeview_image": "", "name": "Triplet Extraction", "is_streaming": true, "uid": "e6ea9179-7d50-4452-b6de-6c71d77213ef", "interaction_view": "", "image": "", "package": "streaming", "static_image": "triplets.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "streaming_triplet_extraction", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Extracts triplets from sentences."}}, {"pk": 4, "model": "workflows.abstractwidget", "fields": {"category": 2, "treeview_image": "", "name": "Triplet graph", "is_streaming": false, "uid": "2734af6c-6044-494d-9f08-4b3526b224c0", "interaction_view": "", "image": "", "package": "base", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "base_triplet_graph", "streaming_visualization_view": "", "action": "base_triplet_graph", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 291, "model": "workflows.abstractwidget", "fields": {"category": 49, "treeview_image": "", "name": "Tuk the Hunter 3D demonstrator", "is_streaming": false, "uid": "ec3279bc-9a20-4e06-84c0-ae0cd1c79a56", "interaction_view": "", "image": "", "package": "MUSE", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "MUSE_virtual_environment_demonstrator_tuk", "streaming_visualization_view": "", "action": "MUSE_virtual_environment_demonstrator_tuk", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "3D demonstrator for the Tuk the Hunter children story"}}, {"pk": 288, "model": "workflows.abstractwidget", "fields": {"category": 49, "treeview_image": "", "name": "Tuk the Hunter 3D demonstrator (local)", "is_streaming": false, "uid": "ac330214-79fe-497e-b7e3-c10ac0af1e1d", "interaction_view": "", "image": "", "package": "MUSE", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "MUSE_virtual_environment_demonstrator_tuk_local", "streaming_visualization_view": "", "action": "MUSE_virtual_environment_demonstrator_tuk_local", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Local copyt of the 3D demonstrator for the Tuk the Hunter children story"}}, {"pk": 211, "model": "workflows.abstractwidget", "fields": {"category": 32, "treeview_image": "", "name": "Tweet Sentiment Analysis", "is_streaming": true, "uid": "62e7f354-d6c7-4c4c-b1b7-795ac613a7e0", "interaction_view": "", "image": "", "package": "streaming", "static_image": "sentiment.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "streaming_tweet_sentiment_service", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Annotates the list of tweets with sentiments, reliability and a corrected language."}}, {"pk": 226, "model": "workflows.abstractwidget", "fields": {"category": 33, "treeview_image": "", "name": "Tweet word cloud", "is_streaming": true, "uid": "e83e17a4-6e8a-40de-8ebe-585503d065e5", "interaction_view": "", "image": "", "package": "streaming", "static_image": "word-cloud.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "streaming_tweet_cloud", "action": "streaming_display_tweets", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 210, "model": "workflows.abstractwidget", "fields": {"category": 32, "treeview_image": "", "name": "Twitter", "is_streaming": true, "uid": "3a929977-0708-4f92-8296-2e109ff0566a", "interaction_view": "", "image": "", "package": "streaming", "static_image": "twitter.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "streaming_twitter", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Queries the twitter API for tweets. Also works in a streaming environment."}}, {"pk": 128, "model": "workflows.abstractwidget", "fields": {"category": 8, "treeview_image": "treeview/UCI-2-ODT.png", "name": "UCI Dataset to Orange Data Table", "is_streaming": false, "uid": "4e8683ae-c571-413c-a592-2093de96e8d1", "interaction_view": "", "image": "images/UCI-2-ODT.png", "package": "cforange", "static_image": "UCI-2-ODT.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "uci_to_odt", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 201, "model": "workflows.abstractwidget", "fields": {"category": 31, "treeview_image": "", "name": "UCI dataset to Scikit Dataset", "is_streaming": false, "uid": "b3918a2b-afab-4225-9c17-5665d4c1a898", "interaction_view": "", "image": "", "package": "scikitAlgorithms", "static_image": "table.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "scikitAlgorithms_UCIDataset", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 41, "model": "workflows.abstractwidget", "fields": {"category": 7, "treeview_image": "", "name": "Union and intersection of attributes for SegMine rule table", "is_streaming": false, "uid": "2e3c0b5c-5bcb-4c8c-950f-a4c92a5d6c7d", "interaction_view": "", "image": "", "package": "segmine", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "segmine_ruletable2attribute_union_intersection", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Returns a set of strings computed as a union and intersection of all attributes of a SegMine rule table (genes or terms)."}}, {"pk": 173, "model": "workflows.abstractwidget", "fields": {"category": 24, "treeview_image": "treeview/viper600-60_1.png", "name": "VIPER: Visual Performance Evaluation", "is_streaming": false, "uid": "4098a678-2d14-4cbe-808d-2d150a7c2341", "interaction_view": "", "image": "images/viper600-60_1.png", "package": "perfeval", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "pr_space_view", "streaming_visualization_view": "", "action": "pr_space", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 289, "model": "workflows.abstractwidget", "fields": {"category": 47, "treeview_image": "", "name": "View XML", "is_streaming": false, "uid": "ca337532-ab9d-4554-afca-b4d14216b156", "interaction_view": "", "image": "", "package": "MUSE", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "MUSE_view_xml", "streaming_visualization_view": "", "action": "MUSE_view_xml", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Displays XML in a modal window"}}, {"pk": 277, "model": "workflows.abstractwidget", "fields": {"category": 49, "treeview_image": "", "name": "Virtual environment visualization", "is_streaming": false, "uid": "05317f75-cc6b-4257-bc71-21f080776bfc", "interaction_view": "", "image": "", "package": "MUSE", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "MUSE_virtual_environment_visualization", "streaming_visualization_view": "", "action": "MUSE_virtual_environment_visualization", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 33, "model": "workflows.abstractwidget", "fields": {"category": 5, "treeview_image": "", "name": "Weighted Sum Model", "is_streaming": false, "uid": "1e086c78-809e-4ef2-886c-95e6deedbdac", "interaction_view": "decision_support_wsm", "image": "", "package": "decision_support", "static_image": "wsm.png", "post_interact_action": "decision_support_wsm_finished", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "decision_support_wsm", "wsdl_method": "", "wsdl": "", "interactive": true, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 307, "model": "workflows.abstractwidget", "fields": {"category": 55, "treeview_image": "", "name": "Weighted forest", "is_streaming": false, "uid": "72a39fab-5433-493f-ae22-12a264075356", "interaction_view": "", "image": "", "package": "big_data", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "wrf_fit", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Weighted forest with MapReduce\r\n\r\nWeighted forest is a novel ensemble algorithm. \r\n\r\nFit phase\r\nWeighted forest algorithm builds multiple decision trees with a bootstrap method on a subset of data. In each tree node, it estimates sqrt(num. of attributes)+1 randomly selected attributes (without replacement). It uses decision tree to predict out-of-bag samples. For each prediction of an out-of-bag sample, it measures margin (classifier confidence in prediction) and leaf identifier that outputs prediction. Algorithm uses similarity matrix, where it stores similarities for each out-of-bag sample that was predicted with the same leaf. We assume that samples are similar, if the same leaf predicts them multiple times in multiple decision trees. \r\nAfter algorithm builds all decision trees, it passes similarity matrix to k-medoids algorithm. Similarity matrix presents distances between test samples. We set parameter k as sqrt(num. of attributes)+1. k-medoids algorithm outputs medoids, which are test samples in the cluster centers of the dataset. Medoids are actual samples in a dataset, unlike centroids which are centers of clusters. Algorithm measures average margin for all samples that are in the cluster of certain medoid. It saves the average margin of a decision tree in its model. Algorithm uses this scores as weights of decision trees in predict phase.\r\nAlgorithm builds a forest on each subset of the data and it merges them in large ensemble. Each forest has its own medoids.\r\n\r\nPredict phase \r\nAlgorithm selects a forest (or more, if it finds equal similarities with medoids in multiple forests), that contain most similar medoid with a test sample. Then it uses the same procedure like with small data. Algorithm calculates Gower similarity coefficient with a test sample and every medoid. Only decision trees with high margin on similar test samples output prediction and algorithm stores decision tree margin for each prediction. Algorithm calculates final values for each prediction: (number of margins) * avg(margins) and it selects prediction with highest value."}}, {"pk": 92, "model": "workflows.abstractwidget", "fields": {"category": 14, "treeview_image": "", "name": "Weka Get Attribute List", "is_streaming": false, "uid": "27b03964-8802-40e5-a7e4-4bed62c305eb", "interaction_view": "", "image": "", "package": "weka", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "weka_get_attr_list", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Returns attribute values for a single attribute from the dataset. Defaults to the last attribute. E.g., useful for calculating classification statistics.\r\n"}}, {"pk": 96, "model": "workflows.abstractwidget", "fields": {"category": 14, "treeview_image": "", "name": "Weka Instances To Arff", "is_streaming": false, "uid": "4d855dc4-0544-484a-914e-79487e8bb982", "interaction_view": "", "image": "", "package": "weka", "static_image": "WEKA_arff.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "call_webservice", "wsdl_method": "weka_instances_to_arff", "wsdl": "http://vihar.ijs.si:8092/Utilities?wsdl", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 107, "model": "workflows.abstractwidget", "fields": {"category": 14, "treeview_image": "", "name": "Weka confusion matrix computations", "is_streaming": false, "uid": "b62a32e0-ab1b-4bf9-b2f2-ed699d4b05be", "interaction_view": "", "image": "", "package": "weka", "static_image": "WEKA_ConfusionMatrix.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "weka_statistics", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Confusion Matrix shows how many instances have been assigned to each class. Elements show the number of test examples whose actual class is the row and whose predicted class is the column."}}, {"pk": 18, "model": "workflows.abstractwidget", "fields": {"category": 2, "treeview_image": "", "name": "Word cloud", "is_streaming": false, "uid": "9c8a4da5-6f43-4dbc-846c-adf280c0f484", "interaction_view": "", "image": "", "package": "base", "static_image": "word-cloud.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "base_wordcloud", "streaming_visualization_view": "", "action": "base_wordcloud", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "Displays a word cloud based on the input string. If the string is a named line documents file (each line starts with !classname) a wordcloud will be displayed for each class."}}, {"pk": 207, "model": "workflows.abstractwidget", "fields": {"category": 32, "treeview_image": "", "name": "WordNet lemmatizer on triplets", "is_streaming": true, "uid": "10957b62-2dcb-4461-8146-70eecf27fcff", "interaction_view": "", "image": "", "package": "streaming", "static_image": "wordnet.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "streaming_triplet_wordnet_lemmatizer", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 85, "model": "workflows.abstractwidget", "fields": {"category": 12, "treeview_image": "treeview/ilp.png", "name": "Wordification", "is_streaming": false, "uid": "63f936a1-6841-44c5-8340-8e4f3fef4f6a", "interaction_view": "", "image": "images/ilp.png", "package": "ilp", "static_image": "ilp.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "ilp_wordification", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 305, "model": "workflows.abstractwidget", "fields": {"category": 56, "treeview_image": "", "name": "k-Means predict", "is_streaming": false, "uid": "6a9edb17-374a-4435-b2b5-85de73714537", "interaction_view": "", "image": "", "package": "big_data", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "kmeans_predict", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": ""}}, {"pk": 198, "model": "workflows.abstractwidget", "fields": {"category": 29, "treeview_image": "", "name": "k-Nearest Neighbours", "is_streaming": false, "uid": "9996e844-67e4-49a6-ac1f-8b64cd72cc1c", "interaction_view": "", "image": "", "package": "scikitAlgorithms", "static_image": "scikit_network.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "scikitAlgorithms_kNearestNeighbors", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "k-Nearest Neighbors classifier based on the ball tree datastructure for low dimensional data and brute force search for high dimensional data.\r\n\r\nn_neighbors: {Natural Numbers} - Number of neighbors to use for k_neighbors queries\r\n\r\nweights : {\u2018uniform\u2019, \u2018distance\u2019,  [callable]}\r\n    \u2018uniform\u2019 : uniform weights. All points in each neighborhood are weighted equally.\r\n    \u2018distance\u2019 : weight points by the inverse of their distance. in this case, closer neighbors of a query point will have a greater influence than neighbors which are further away.\r\n    [callable] : a user-defined function which accepts an array of distances, and returns an array of the same shape containing the weights.\r\n\r\n\r\nalgorithm : {\u2018auto\u2019, \u2018ball_tree\u2019, \u2018kd_tree\u2019, \u2018brute\u2019} - Algorithm used to compute the nearest neighbors:\r\n    \u2018ball_tree\u2019 will use BallTree\r\n    \u2018kd_tree\u2019 will use scipy.spatial.cKDtree\r\n    \u2018brute\u2019 will use a brute-force search.\r\n    \u2018auto\u2019 will attempt to decide the most appropriate algorithm based on the values passed to fit method.\r\n\r\n"}}, {"pk": 310, "model": "workflows.abstractwidget", "fields": {"category": 56, "treeview_image": "", "name": "k-means", "is_streaming": false, "uid": "83c90b6f-9fc1-43d5-a144-6d539497351e", "interaction_view": "", "image": "", "package": "big_data", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "kmeans_fit", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 1, "description": "kmeans with MapReduce\r\n\r\nThe k-means is a partitional clustering technique that attempts to find a user-specified number of clusters k represented by their centroids."}}, {"pk": 27, "model": "workflows.abstractwidget", "fields": {"category": 3, "treeview_image": "treeview/d914a910_2.png", "name": "Add multiple integers", "is_streaming": false, "uid": "e327e9ce-0a1d-4dcc-90ac-45ea4fd74707", "interaction_view": "", "image": "images/d914a910_2.png", "package": "base", "static_image": "d914a910_2.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "add_multiple", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 2, "description": ""}}, {"pk": 147, "model": "workflows.abstractwidget", "fields": {"category": 18, "treeview_image": "", "name": "Brier Score", "is_streaming": false, "uid": "a8e19b70-c295-484c-acca-8ce12c489793", "interaction_view": "", "image": "", "package": "cforange", "static_image": "BS.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "cforange_brier_score", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 2, "description": "Computes the Brier's score, defined as the average (over test examples) of sumx(t(x)-p(x))^2, where x is a class, t(x) is 1 for the correct class and 0 for the others, and p(x) is the probability that the classifier assigned to the class x."}}, {"pk": 125, "model": "workflows.abstractwidget", "fields": {"category": 17, "treeview_image": "treeview/Orange-BuildClassifier.png", "name": "Build Classifier", "is_streaming": false, "uid": "39809f9a-3742-4ca0-908a-1d8a041261af", "interaction_view": "", "image": "images/Orange-BuildClassifier.png", "package": "cforange", "static_image": "Orange-BuildClassifier.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "build_classifier", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 2, "description": ""}}, {"pk": 249, "model": "workflows.abstractwidget", "fields": {"category": 36, "treeview_image": "", "name": "Build default vocabulary with custom compounds", "is_streaming": false, "uid": "78b1895b-362e-4416-a21c-ccf4df74334a", "interaction_view": "", "image": "", "package": "bio3graph", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "bio3graph_build_default_vocabulary_custom_compounds", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 2, "description": "Constructs a default Bio3graph vocabulary but with custom compounds."}}, {"pk": 141, "model": "workflows.abstractwidget", "fields": {"category": 22, "treeview_image": "treeview/orange-CN2-small.png", "name": "CN2 Rule Learner", "is_streaming": false, "uid": "766ef980-6622-4168-b4c5-60c5001dba8b", "interaction_view": "", "image": "images/orange-CN2-small.png", "package": "cforange", "static_image": "orange-CN2-small.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "cn2", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 2, "description": "Use this widget to learn a set of if-then rules from data. 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"Create-Range_1.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "create_range", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 2, "description": ""}}, {"pk": 1, "model": "workflows.abstractwidget", "fields": {"category": 2, "treeview_image": "treeview/string.png", "name": "Create String", "is_streaming": false, "uid": "1b38bbab-7f89-4469-94cd-2f481f9c61f7", "interaction_view": "", "image": "images/string.png", "package": "base", "static_image": "string.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "create_string", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 2, "description": "Creates a string"}}, {"pk": 304, "model": "workflows.abstractwidget", "fields": {"category": 52, "treeview_image": "", "name": "Gaussian Naive Bayes predict", "is_streaming": false, "uid": "672a3a70-1bd9-4c99-b55a-e5fe8fc5c264", "interaction_view": "", "image": "", "package": "big_data", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "gaussian_naive_bayes_predict", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 2, "description": ""}}, {"pk": 19, "model": "workflows.abstractwidget", "fields": {"category": 4, "treeview_image": "", "name": "Load big file", "is_streaming": false, "uid": "a9a75284-37d6-4520-a30b-30005f08c5d2", "interaction_view": "", "image": "", "package": "base", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "base_load_big_file", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 2, "description": ""}}, {"pk": 32, "model": "workflows.abstractwidget", "fields": {"category": 4, "treeview_image": "treeview/Upload-icon.png", "name": "Load file", "is_streaming": false, "uid": "ff4e5d1a-c09b-4c1c-85e0-190c3b933418", "interaction_view": "", "image": "images/Upload-icon.png", "package": "base", "static_image": "Upload-icon.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "load_file", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 2, "description": ""}}, {"pk": 66, "model": "workflows.abstractwidget", "fields": {"category": 9, "treeview_image": "", "name": "Query data with subgroups", "is_streaming": false, "uid": "920cd259-b727-4f88-b4a6-bea0c3ea60b1", "interaction_view": "", "image": "", "package": "subgroup_discovery", "static_image": "querydatawithsg.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "query_with_subgroups", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 2, "description": ""}}, {"pk": 275, "model": "workflows.abstractwidget", "fields": {"category": 44, "treeview_image": "", "name": "ROC curves", "is_streaming": false, "uid": "f8e7ead9-1ed0-43e1-9c93-01087fa1470a", "interaction_view": "", "image": "", "package": "vipercharts", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "vipercharts_roc_curve_view", "streaming_visualization_view": "", "action": "vipercharts_roc_curve", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 2, "description": ""}}, {"pk": 300, "model": "workflows.abstractwidget", "fields": {"category": 51, "treeview_image": "", "name": "Results View", "is_streaming": false, "uid": "437156da-ad2c-41d0-b20b-a10e746e35c2", "interaction_view": "", "image": "", "package": "big_data", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "results_to_file", "streaming_visualization_view": "", "action": "results_to_file", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 2, "description": ""}}, {"pk": 245, "model": "workflows.abstractwidget", "fields": {"category": 36, "treeview_image": "", "name": "Build vocabulary", "is_streaming": false, "uid": "52ca48b5-0efe-4bfb-a559-5b3f903149a8", "interaction_view": "", "image": "", "package": "bio3graph", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "bio3graph_build_vocabulary", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 3, "description": "Constructs a Bio3graph vocabulary for triplet extraction using the provided files."}}, {"pk": 153, "model": "workflows.abstractwidget", "fields": {"category": 18, "treeview_image": "", "name": "Classification Accuracy", "is_streaming": false, "uid": "c3554695-87ec-43a7-8bac-f6738f462a09", "interaction_view": "", "image": "", "package": "cforange", "static_image": "CA.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "cforange_classification_accuracy", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 3, "description": "Computes classification accuracy, i.e. percentage of matches between predicted and actual class. The function returns a list of classification accuracies of all classifiers tested. If reportSE is set to true, the list will contain tuples with accuracies and standard errors."}}, {"pk": 124, "model": "workflows.abstractwidget", "fields": {"category": 22, "treeview_image": "treeview/orange-ClassificationTree.png", "name": "Classification Tree", "is_streaming": false, "uid": "29b5871f-1829-4af6-8463-c6515e2010c6", "interaction_view": "", "image": "images/orange-ClassificationTree.png", "package": "cforange", "static_image": "orange-ClassificationTree.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "class_tree", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 3, "description": "Classification Tree Learner. "}}, {"pk": 276, "model": "workflows.abstractwidget", "fields": {"category": 17, "treeview_image": "", "name": "Compare actual and predicted class", "is_streaming": false, "uid": "fba38909-b392-4f6e-bff0-d6e321d646f9", "interaction_view": "", "image": "", "package": "vipercharts", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "vipercharts_compare_class_ActualPredicted_orange", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 3, "description": ""}}, {"pk": 14, "model": "workflows.abstractwidget", "fields": {"category": 3, "treeview_image": "treeview/417px-Latex_integers.svg.png", "name": "Create Integer", "is_streaming": false, "uid": "8b20d4ad-c420-4156-973d-48d6d15934ba", "interaction_view": "", "image": "images/417px-Latex_integers.svg.png", "package": "base", "static_image": "417px-Latex_integers.svg.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "create_integer", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 3, "description": "Creates an integer object from a parameter."}}, {"pk": 11, "model": "workflows.abstractwidget", "fields": {"category": 1, "treeview_image": "treeview/482063585452602669.png", "name": "Delay", "is_streaming": false, "uid": "51a88c36-60c3-44c1-ba5a-b895c0ed0370", "interaction_view": "", "image": "images/482063585452602669.png", "package": "base", "static_image": "482063585452602669.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "delay", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": true, "order": 3, "description": "Delays for a certain amount of seconds"}}, {"pk": 6, "model": "workflows.abstractwidget", "fields": {"category": 2, "treeview_image": "treeview/display_string.png", "name": "Display String", "is_streaming": false, "uid": "2c69b211-05fe-49a2-8de1-d38971e75b95", "interaction_view": "", "image": "images/display_string.png", "package": "base", "static_image": "display_string.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "display_string", "streaming_visualization_view": "", "action": "display_string", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 3, "description": ""}}, {"pk": 303, "model": "workflows.abstractwidget", "fields": {"category": 52, "treeview_image": "", "name": "Linear SVM", "is_streaming": false, "uid": "4fddd2e5-f253-4854-a246-389ce6cce36c", "interaction_view": "", "image": "", "package": "big_data", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "linsvm_fit", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 3, "description": "Linear proximal SVM with MapReduce\r\n\r\nAlgorithm builds a model with continuous features and predicts binary target label (-1, 1). \r\n\r\nReference\r\nAlgorithm is proposed by Glenn Fung, O. 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"}}, {"pk": 13, "model": "workflows.abstractwidget", "fields": {"category": 4, "treeview_image": "treeview/Upload-icon_1.png", "name": "Load file to string", "is_streaming": false, "uid": "866b596e-0131-43f6-969d-97f43c66ef0d", "interaction_view": "", "image": "images/Upload-icon_1.png", "package": "base", "static_image": "Upload-icon_1.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "load_to_string", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 3, "description": ""}}, {"pk": 274, "model": "workflows.abstractwidget", "fields": {"category": 44, "treeview_image": "", "name": "ROC hull curves", "is_streaming": false, "uid": "cad2f550-d65b-4281-bdb2-fdf48193f669", "interaction_view": "", "image": "", "package": "vipercharts", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "vipercharts_roc_hull_view", "streaming_visualization_view": "", "action": "vipercharts_roc_hull", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 3, "description": ""}}, {"pk": 65, "model": "workflows.abstractwidget", "fields": {"category": 9, "treeview_image": "", "name": "Select subgroups", "is_streaming": false, "uid": "6e02a8d4-fe84-4430-8a74-beb1e4c51964", "interaction_view": "select_subgroups", "image": "", "package": "subgroup_discovery", "static_image": "selectsg.png", "post_interact_action": "select_subgroups_finished", "windows_queue": false, "user": null, "visualization_view": "select_subgroups", "streaming_visualization_view": "", "action": "select_subgroups", "wsdl_method": "", "wsdl": "", "interactive": true, "has_progress_bar": false, "order": 3, "description": ""}}, {"pk": 242, "model": "workflows.abstractwidget", "fields": {"category": 37, "treeview_image": "", "name": "Colour relations", "is_streaming": false, "uid": "2ba518b9-b65f-4569-a7ea-0fc9a2ce98ea", "interaction_view": "", "image": "", "package": "bio3graph", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "bio3graph_colour_relations", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 4, "description": "Colours given relations in a given graph. Pink colour is used."}}, {"pk": 132, "model": "workflows.abstractwidget", "fields": {"category": 18, "treeview_image": "", "name": "Confusion Matrix", "is_streaming": false, "uid": "5cab835b-82f8-4146-a4d0-ff3b3f923395", "interaction_view": "", "image": "", "package": "cforange", "static_image": "ConfusionMatrix_60.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "cforange_confusion_matrix", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 4, "description": "Confusion Matrix gives the number/proportion of examples from one class classified in to another (or same) class. Besides that, selecting elements of the matrix feeds the corresponding examples onto the output signal. 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A logistic regression classification model stores estimated values of regression coefficients and their significances, and uses them to predict classes and class probabilities."}}, {"pk": 189, "model": "workflows.abstractwidget", "fields": {"category": 29, "treeview_image": "", "name": "Naive Bayes", "is_streaming": false, "uid": "14161bcf-f025-47a4-abe9-a34ec848cf1c", "interaction_view": "", "image": "", "package": "scikitAlgorithms", "static_image": "scikit_NaiveBayes_60.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "scikitAlgorithms_naiveBayes", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 4, "description": "implements the Naive Bayes algorithm for classification. "}}, {"pk": 269, "model": "workflows.abstractwidget", "fields": {"category": 44, "treeview_image": "", "name": "PR curves", "is_streaming": false, "uid": "9d38dbab-1a07-46e8-b551-019a50a2d7f9", "interaction_view": "", "image": "", "package": "vipercharts", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "vipercharts_pr_curve_view", "streaming_visualization_view": "", "action": "vipercharts_pr_curve", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 4, "description": ""}}, {"pk": 263, "model": "workflows.abstractwidget", "fields": {"category": 17, "treeview_image": "", "name": "Select Class from ODT", "is_streaming": false, "uid": "14b90c25-47ae-4df1-8781-de2baad6cff3", "interaction_view": "class_from_odt_interactive", "image": "", "package": "vipercharts", "static_image": "", "post_interact_action": "class_from_odt_selection", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "class_from_odt", "wsdl_method": "", "wsdl": "", "interactive": true, "has_progress_bar": false, "order": 4, "description": ""}}, {"pk": 10, "model": "workflows.abstractwidget", "fields": {"category": 4, "treeview_image": "treeview/1688041475.png", "name": "String to file", "is_streaming": false, "uid": "442f5484-494d-4bd7-b1c2-74c1153dd1fe", "interaction_view": "", "image": "images/1688041475.png", "package": "base", "static_image": "1688041475.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "string_to_file", "streaming_visualization_view": "", "action": "string_to_file", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 4, "description": ""}}, {"pk": 67, "model": "workflows.abstractwidget", "fields": {"category": 9, "treeview_image": "", "name": "Subgroup ROC visualization", "is_streaming": false, "uid": "b05c5df4-d3fb-44e6-b647-b4c5f78c05cf", "interaction_view": "", "image": "", "package": "subgroup_discovery", "static_image": "roc.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "subgroup_roc_visualization", "streaming_visualization_view": "", "action": "subgroup_roc_visualization", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 4, "description": ""}}, {"pk": 64, "model": "workflows.abstractwidget", "fields": {"category": 9, "treeview_image": "", "name": "Subgroup measures", "is_streaming": false, "uid": "2df99021-b221-4dae-a264-5139918c3920", "interaction_view": "", "image": "", "package": "subgroup_discovery", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "subgroup_measures", "streaming_visualization_view": "", "action": "subgroup_measures", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 4, "description": ""}}, {"pk": 143, "model": "workflows.abstractwidget", "fields": {"category": 18, "treeview_image": "", "name": "Confusion Matrix Computations", "is_streaming": false, "uid": "7ac99069-f563-4580-a0de-2aa79b47ff4b", "interaction_view": "", "image": "", "package": "cforange", "static_image": "ConfusionMatrix_60.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "cforange_confusion_matrix_computations", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 5, "description": "With the confusion matrix defined in terms of positive and negative classes, you can also compute the sensitivity [TP/(TP+FN)], specificity [TN/(TN+FP)], positive predictive value [TP/(TP+FP)] and negative predictive value [TN/(TN+FN)]. In information retrieval, positive predictive value is called precision (the ratio of the number of relevant records retrieved to the total number of irrelevant and relevant records retrieved), and sensitivity is called recall (the ratio of the number of relevant records retrieved to the total number of relevant records in the database). The harmonic mean of precision and recall is called an F-measure, where, depending on the ratio of the weight between precision and recall is implemented as F1 [2*precision*recall/(precision+recall)] or, for a general case, Falpha [(1+alpha)*precision*recall / (alpha*precision + recall)]."}}, {"pk": 244, "model": "workflows.abstractwidget", "fields": {"category": 35, "treeview_image": "", "name": "Construct compounds csv file from gene synonyms", "is_streaming": false, "uid": "5016b669-4b80-440d-9da6-66e81b64a145", "interaction_view": "", "image": "", "package": "bio3graph", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "bio3graph_construct_compounds_from_gene_synonyms", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 5, "description": "Constructs a csv file from gene synonyms dictionary"}}, {"pk": 265, "model": "workflows.abstractwidget", "fields": {"category": 44, "treeview_image": "", "name": "Cost curves", "is_streaming": false, "uid": "6204d7f1-185c-489b-a8c3-4c2188fa380a", "interaction_view": "", "image": "", "package": "vipercharts", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "vipercharts_cost_curve_view", "streaming_visualization_view": "", "action": "vipercharts_cost_curve", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 5, "description": ""}}, {"pk": 297, "model": "workflows.abstractwidget", "fields": {"category": 52, "treeview_image": "", "name": "Logistic regression", "is_streaming": false, "uid": "16042741-6834-43ab-9587-b64a1f460238", "interaction_view": "", "image": "", "package": "big_data", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "logreg_fit", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 5, "description": "Logistic regression with MapReduce\r\n\r\nAlgorithm builds a model with continuous features and predicts binary target variable (1, 0). Learning is done by fitting theta parameters to the training data where the likelihood function is optimized by using Newton-Raphson to update theta parameters. The output of algorithm is consistent with implementation of logistic regression classifier in Orange.\r\n\r\nReference:\r\nMapReduce version of algorithm is proposed by Cheng-Tao Chu; Sang Kyun Kim, Yi-An Lin, YuanYuan Yu, Gary Bradski, Andrew Ng, and Kunle Olukotun. \"Map-Reduce for Machine Learning on Multicore\". NIPS 2006. "}}, {"pk": 121, "model": "workflows.abstractwidget", "fields": {"category": 22, "treeview_image": "treeview/lookup.png", "name": "Lookup Learner", "is_streaming": false, "uid": "1781ee2a-f353-42b4-96d4-3379329c984e", "interaction_view": "", "image": "images/lookup.png", "package": "cforange", "static_image": "lookup.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "lookup_learner", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 5, "description": "Lookup classifiers predict classes by looking into stored lists of cases. A learner sorts the data instances and merges those with the same feature values."}}, {"pk": 22, "model": "workflows.abstractwidget", "fields": {"category": 3, "treeview_image": "", "name": "Multiply integers", "is_streaming": false, "uid": "c950af9c-be87-4761-a69e-e37f0c26cacb", "interaction_view": "", "image": "", "package": "base", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "multiply_integers", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 5, "description": ""}}, {"pk": 17, "model": "workflows.abstractwidget", "fields": {"category": 1, "treeview_image": "treeview/glass_1.png", "name": "Object viewer", "is_streaming": false, "uid": "9c7ff1bd-6026-4ebd-b44f-ed889a8b0fad", "interaction_view": "", "image": "images/glass_3.png", "package": "base", "static_image": "glass_3.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "object_viewer", "streaming_visualization_view": "", "action": "object_viewer", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 5, "description": "Displays any input."}}, {"pk": 68, "model": "workflows.abstractwidget", "fields": {"category": 9, "treeview_image": "", "name": "Subgroup bar visualization", "is_streaming": false, "uid": "b3cb0462-6bae-4922-a67d-504e93fc0fc6", "interaction_view": "", "image": "", "package": "subgroup_discovery", "static_image": "bar.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "subgroup_bar_visualization", "streaming_visualization_view": "", "action": "subgroup_bar_visualization", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 5, "description": ""}}, {"pk": 235, "model": "workflows.abstractwidget", "fields": {"category": 37, "treeview_image": "", "name": "Construct triplet network", "is_streaming": false, "uid": "116f578f-a366-4767-94fe-c08f9b40faec", "interaction_view": "", "image": "", "package": "bio3graph", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "bio3graph_construct_triplet_network", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 6, "description": "Constructs a network from input triplets. Biomine's .bmg format as well as NetworkX data structure is produced."}}, {"pk": 164, "model": "workflows.abstractwidget", "fields": {"category": 18, "treeview_image": "", "name": "Correct Class Average Probability", "is_streaming": false, "uid": "e21925ad-fdc3-487d-944e-5eb03caa2350", "interaction_view": "", "image": "", "package": "cforange", "static_image": "CCAP.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "cforange_average_probability", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 6, "description": "Computes the average probability assigned to the correct class."}}, {"pk": 266, "model": "workflows.abstractwidget", "fields": {"category": 44, "treeview_image": "", "name": "Kendall curves", "is_streaming": false, "uid": "88dfe77b-6289-4a9b-987b-e9a1fbdb08a7", "interaction_view": "", "image": "", "package": "vipercharts", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "vipercharts_kendall_curve_view", "streaming_visualization_view": "", "action": "vipercharts_kendall_curve", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 6, "description": ""}}, {"pk": 315, "model": "workflows.abstractwidget", "fields": {"category": 52, "treeview_image": "", "name": "Logistic regression predict", "is_streaming": false, "uid": "dd67df4e-7c84-4d0e-aa7f-6c94ebd0356a", "interaction_view": "", "image": "", "package": "big_data", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "log_reg_predict", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 6, "description": "The logistic regression classifier is a binary classifier that uses numeric features. The classifier learns by fitting theta parameters to the training data using Newton-Raphson method to update theta parameters."}}, {"pk": 167, "model": "workflows.abstractwidget", "fields": {"category": 22, "treeview_image": "treeview/orange-Majority.png", "name": "Majority Learner", "is_streaming": false, "uid": "f11eaa13-d94b-40e1-adfb-a811ae36bc2d", "interaction_view": "", "image": "images/orange-Majority.png", "package": "cforange", "static_image": "orange-Majority.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "majority_learner", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 6, "description": "A Learner that returns the majority class, disregarding the example\u2019s attributes. Accuracy of classifiers is often compared with the \u201cdefault accuracy\u201d, that is, the accuracy of a classifier which classifies all instances to the majority class. The training of such classifier consists of computing the class distribution and its modus. This \u201clearning algorithm\u201d will most often be used as a baseline, that is, to determine if some other learning algorithm provides any information about the class."}}, {"pk": 2, "model": "workflows.abstractwidget", "fields": {"category": 1, "treeview_image": "treeview/pickle.png", "name": "Pickle object", "is_streaming": false, "uid": "1f6bd626-331e-4ac3-b55f-cec8fcd8fd9e", "interaction_view": "", "image": "images/pickle.png", "package": "base", "static_image": "pickle.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "pickle_object", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 6, "description": ""}}, {"pk": 21, "model": "workflows.abstractwidget", "fields": {"category": 3, "treeview_image": "treeview/d914a910_1.png", "name": "Subtract integers", "is_streaming": false, "uid": "c6cf5c17-f6a6-4076-bf35-ecb06d72da86", "interaction_view": "", "image": "images/d914a910_1.png", "package": "base", "static_image": "d914a910_1.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "subtract_integers", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 6, "description": "Subtracts two integers"}}, {"pk": 239, "model": "workflows.abstractwidget", "fields": {"category": 36, "treeview_image": "", "name": "Create document from file", "is_streaming": false, "uid": "217e7a3e-6576-47a2-bd61-62e7e5a0e1c5", "interaction_view": "", "image": "", "package": "bio3graph", "static_image": "", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "bio3graph_create_document_from_file", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 7, "description": "Creates a document object structure from a given file."}}, {"pk": 133, "model": "workflows.abstractwidget", "fields": {"category": 18, "treeview_image": "", "name": "Information Score", "is_streaming": false, "uid": "5fed0e33-c267-4522-a4ff-faf745e80be6", "interaction_view": "", "image": "", "package": "cforange", "static_image": "IS.png", "post_interact_action": "", "windows_queue": false, "user": null, "visualization_view": "", "streaming_visualization_view": "", "action": "cforange_information_score", "wsdl_method": "", "wsdl": "", "interactive": false, "has_progress_bar": false, "order": 7, "description": "Computes the information score as defined by Kononenko and Bratko (1991). 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