{"run":{"run_id":"965049","uploader":"1","uploader_name":"Jan van Rijn","task_id":"56211","task_type":"Subgroup Discovery","flow_id":"4221","flow_name":"SubgroupDiscovery(1)","setup_id":"7997","error":[],"setup_string":"{\"overall_ranking_loss\":\"0.0\",\"post_processing_count\":\"20\",\"search_depth\":\"2\",\"maximum_time\":\"1.0\",\"search_strategy_width\":\"4\",\"numeric_strategy\":\"best-bins\",\"numeric_operators\":\"≤, ≥, =<\\\/html>\",\"beta\":\"1.0\",\"minimum_coverage\":\"2\",\"nr_threads\":\"1\",\"search_strategy\":\"beam\",\"alpha\":\"0.5\",\"beam_seed\":\"\",\"use_nominal_sets\":\"false\",\"maximum_coverage_fraction\":\"1.0\",\"post_processing_do_autorun\":\"true\",\"nr_bins\":\"64\",\"maximum_subgroups\":\"100\"}","parameter_setting":[{"name":"search_depth","value":"2","component":"4221"},{"name":"minimum_coverage","value":"2","component":"4221"},{"name":"maximum_coverage_fraction","value":"1.0","component":"4221"},{"name":"maximum_subgroups","value":"100","component":"4221"},{"name":"maximum_time","value":"1.0","component":"4221"},{"name":"search_strategy","value":"beam","component":"4221"},{"name":"use_nominal_sets","value":"false","component":"4221"},{"name":"search_strategy_width","value":"4","component":"4221"},{"name":"numeric_operators","value":"≤, ≥, =<\/html>","component":"4221"},{"name":"numeric_strategy","value":"best-bins","component":"4221"},{"name":"nr_bins","value":"64","component":"4221"},{"name":"nr_threads","value":"1","component":"4221"},{"name":"alpha","value":"0.5","component":"4221"},{"name":"beta","value":"1.0","component":"4221"},{"name":"post_processing_do_autorun","value":"true","component":"4221"},{"name":"post_processing_count","value":"20","component":"4221"},{"name":"beam_seed","value":[],"component":"4221"},{"name":"overall_ranking_loss","value":"0.0","component":"4221"}],"tag":"Cortana","input_data":{"dataset":{"did":"1494","name":"qsar-biodeg","url":"https:\/\/www.openml.org\/data\/download\/1592286\/phpGUrE90"}},"output_data":{"file":[{"did":"-1","file_id":"2804615","name":"description","url":"https:\/\/www.openml.org\/data\/download\/2804615\/run4918098685323838376.xml"},{"did":"-1","file_id":"2804616","name":"subgroups","url":"https:\/\/www.openml.org\/data\/download\/2804616\/subgroups8205479779234358156.csv"}],"evaluation":[{"name":"cortana_quality","value":"0.545631","array_data":"[0.545631, 0.5397518, 0.5397518, 0.5342906, 0.5341339, 0.5310636, 0.5238583, 0.5221464, 0.5201934, 0.5197755, 0.5179791, 0.516862, 0.5153791, 0.5123089, 0.5107216, 0.5096567, 0.5094477, 0.5093432, 0.5093432, 0.5092909, 0.5080171, 0.5078604, 0.5078604, 0.5064819, 0.5037774, 0.5033395, 0.5027447, 0.5022424, 0.5021901, 0.5021901, 0.5021379, 0.5009162, 0.5008118, 0.5007073, 0.5003215, 0.4996423, 0.4993289, 0.4993289, 0.4993289, 0.4989954, 0.4984207, 0.4983684, 0.4981073, 0.4980028, 0.4979505, 0.4966244, 0.4966244, 0.4965721, 0.4964476, 0.4964476, 0.494599, 0.4941811, 0.4937631, 0.4937631, 0.4937631, 0.4937631, 0.4937631, 0.4937631, 0.4935341, 0.4933251, 0.4933251, 0.4925415, 0.4925415, 0.4924169, 0.4923325, 0.4922803, 0.4921035, 0.4906729, 0.4902549, 0.4895236, 0.4895236, 0.4888042, 0.4880929, 0.4875504, 0.4873415, 0.4852839, 0.4852839, 0.4852839, 0.4845847, 0.4845847, 0.4832063, 0.4832063, 0.4810444, 0.4808675, 0.4805018, 0.4799593, 0.479019, 0.4787055, 0.4780385, 0.4776406, 0.4720226, 0.4715525, 0.4715525, 0.4715324, 0.4713435, 0.4701218, 0.4688801, 0.4687435, 0.4677308, 0.4676263]"},{"name":"coverage","value":"398","array_data":"[398, 411, 411, 400, 409, 423, 431, 367, 398, 422, 444, 427, 431, 445, 455, 435, 447, 453, 453, 456, 448, 457, 457, 455, 448, 392, 345, 455, 458, 458, 461, 450, 456, 462, 403, 442, 460, 460, 460, 398, 431, 434, 449, 455, 458, 453, 453, 456, 382, 382, 407, 431, 455, 455, 455, 455, 455, 455, 387, 399, 399, 444, 444, 370, 456, 459, 388, 389, 413, 455, 455, 334, 456, 406, 418, 455, 455, 455, 414, 414, 412, 412, 455, 384, 405, 355, 409, 427, 303, 407, 405, 432, 432, 352, 444, 433, 342, 431, 408, 414]"},{"name":"positives","value":"263","array_data":"[263, 266, 266, 261, 264, 268, 269, 247, 257, 265, 272, 266, 267, 271, 274, 267, 271, 273, 273, 274, 271, 274, 274, 273, 270, 251, 235, 272, 273, 273, 274, 270, 272, 274, 254, 267, 273, 273, 273, 252, 263, 264, 269, 271, 272, 270, 270, 271, 246, 246, 254, 262, 270, 270, 270, 270, 270, 270, 247, 251, 251, 266, 266, 241, 270, 271, 247, 247, 255, 269, 269, 228, 269, 252, 256, 268, 268, 268, 254, 254, 253, 253, 267, 243, 250, 233, 251, 257, 215, 250, 248, 257, 257, 230, 261, 257, 226, 256, 248, 250]"},{"name":"probability","value":"0.660804","array_data":"[0.660804, 0.6472019, 0.6472019, 0.6525, 0.6454768, 0.6335697, 0.6241299, 0.6730245, 0.6457286, 0.6279621, 0.6126126, 0.6229508, 0.6194896, 0.6089888, 0.6021978, 0.6137931, 0.606264, 0.602649, 0.602649, 0.6008772, 0.6049107, 0.5995624, 0.5995624, 0.6, 0.6026786, 0.6403061, 0.6811594, 0.5978022, 0.5960699, 0.5960699, 0.5943601, 0.6, 0.5964912, 0.5930736, 0.630273, 0.6040724, 0.5934783, 0.5934783, 0.5934783, 0.6331658, 0.6102088, 0.6082949, 0.5991091, 0.5956044, 0.5938865, 0.5960265, 0.5960265, 0.5942982, 0.6439791, 0.6439791, 0.6240786, 0.6078886, 0.5934066, 0.5934066, 0.5934066, 0.5934066, 0.5934066, 0.5934066, 0.6382429, 0.6290727, 0.6290727, 0.5990991, 0.5990991, 0.6513514, 0.5921053, 0.5904139, 0.6365979, 0.6349614, 0.6174334, 0.5912088, 0.5912088, 0.6826347, 0.5899123, 0.6206897, 0.6124402, 0.589011, 0.589011, 0.589011, 0.6135266, 0.6135266, 0.6140777, 0.6140777, 0.5868132, 0.6328125, 0.617284, 0.656338, 0.6136919, 0.6018735, 0.709571, 0.6142506, 0.6123457, 0.5949074, 0.5949074, 0.6534091, 0.5878378, 0.5935335, 0.6608187, 0.5939675, 0.6078431, 0.6038647]"},{"name":"joint_entropy","value":"4.589577130205673"},{"name":"pattern_team_auroc10","value":"0.7832517561203003"}]}}}