Task
Supervised Classification on autoMpg

Supervised Classification on autoMpg

Task 3696 Supervised Classification autoMpg 504 runs submitted
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  • mythbusting_1 study_1 study_107 study_123 study_15 study_20 study_41 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9626, build_cpu_time: 0.0425, build_memory: 2541290617.4673, f_measure: 0.9171, kappa: 0.834, kb_relative_information_score: 305.5879, mean_absolute_error: 0.1243, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9177, predictive_accuracy: 0.9171, prior_entropy: 0.9982, recall: 0.9171, relative_absolute_error: 0.2493, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2496, root_relative_squared_error: 0.4999, scimark_benchmark: 940.8303,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9667, f_measure: 0.8919, kappa: 0.7846, kb_relative_information_score: 310.3361, mean_absolute_error: 0.1099, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.8978, predictive_accuracy: 0.892, prior_entropy: 0.9982, recall: 0.892, relative_absolute_error: 0.2204, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3089, root_relative_squared_error: 0.6187, scimark_benchmark: 932.5646,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9607, f_measure: 0.912, kappa: 0.8236, kb_relative_information_score: 295.3716, mean_absolute_error: 0.1387, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.912, predictive_accuracy: 0.9121, prior_entropy: 0.9982, recall: 0.9121, relative_absolute_error: 0.2781, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2582, root_relative_squared_error: 0.5171, scimark_benchmark: 1318.6096, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9767, f_measure: 0.9347, kappa: 0.8693, kb_relative_information_score: 329.6642, mean_absolute_error: 0.0898, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9359, predictive_accuracy: 0.9347, prior_entropy: 0.9982, recall: 0.9347, relative_absolute_error: 0.18, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.233, root_relative_squared_error: 0.4665, scimark_benchmark: 1405.2896,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9625, f_measure: 0.9171, kappa: 0.8341, kb_relative_information_score: 326.3357, mean_absolute_error: 0.0915, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9181, predictive_accuracy: 0.9171, prior_entropy: 0.9982, recall: 0.9171, relative_absolute_error: 0.1834, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2634, root_relative_squared_error: 0.5275, scimark_benchmark: 1322.0065, usercpu_time_millis: 100, usercpu_time_millis_training: 100,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9767, f_measure: 0.9347, kappa: 0.8693, kb_relative_information_score: 329.6642, mean_absolute_error: 0.0898, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9359, predictive_accuracy: 0.9347, prior_entropy: 0.9982, recall: 0.9347, relative_absolute_error: 0.18, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.233, root_relative_squared_error: 0.4665, scimark_benchmark: 1303.5632,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9759, f_measure: 0.9221, kappa: 0.8439, kb_relative_information_score: 313.8115, mean_absolute_error: 0.1118, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9223, predictive_accuracy: 0.9221, prior_entropy: 0.9982, recall: 0.9221, relative_absolute_error: 0.2241, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2415, root_relative_squared_error: 0.4837, scimark_benchmark: 1371.9645, usercpu_time_millis: 3200, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 3170,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9767, f_measure: 0.9347, kappa: 0.8693, kb_relative_information_score: 329.6642, mean_absolute_error: 0.0898, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9359, predictive_accuracy: 0.9347, prior_entropy: 0.9982, recall: 0.9347, relative_absolute_error: 0.18, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.233, root_relative_squared_error: 0.4665, scimark_benchmark: 1347.993,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9667, f_measure: 0.8919, kappa: 0.7846, kb_relative_information_score: 310.3361, mean_absolute_error: 0.1099, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.8978, predictive_accuracy: 0.892, prior_entropy: 0.9982, recall: 0.892, relative_absolute_error: 0.2204, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3089, root_relative_squared_error: 0.6187, scimark_benchmark: 1260.1387,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9809, f_measure: 0.9347, kappa: 0.8691, kb_relative_information_score: 315.4704, mean_absolute_error: 0.1108, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9348, predictive_accuracy: 0.9347, prior_entropy: 0.9982, recall: 0.9347, relative_absolute_error: 0.2222, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2332, root_relative_squared_error: 0.467, scimark_benchmark: 1322.7257, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9767, f_measure: 0.9347, kappa: 0.8693, kb_relative_information_score: 329.6642, mean_absolute_error: 0.0898, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9359, predictive_accuracy: 0.9347, prior_entropy: 0.9982, recall: 0.9347, relative_absolute_error: 0.18, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.233, root_relative_squared_error: 0.4665, scimark_benchmark: 1347.993,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9667, f_measure: 0.8919, kappa: 0.7846, kb_relative_information_score: 310.3361, mean_absolute_error: 0.1099, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.8978, predictive_accuracy: 0.892, prior_entropy: 0.9982, recall: 0.892, relative_absolute_error: 0.2204, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3089, root_relative_squared_error: 0.6187, scimark_benchmark: 938.0414, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9809, f_measure: 0.9347, kappa: 0.8691, kb_relative_information_score: 315.4704, mean_absolute_error: 0.1108, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9348, predictive_accuracy: 0.9347, prior_entropy: 0.9982, recall: 0.9347, relative_absolute_error: 0.2222, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2332, root_relative_squared_error: 0.467, scimark_benchmark: 942.9708, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9607, f_measure: 0.912, kappa: 0.8236, kb_relative_information_score: 295.3716, mean_absolute_error: 0.1387, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.912, predictive_accuracy: 0.9121, prior_entropy: 0.9982, recall: 0.9121, relative_absolute_error: 0.2781, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2582, root_relative_squared_error: 0.5171, scimark_benchmark: 1347.993, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9759, f_measure: 0.9221, kappa: 0.8439, kb_relative_information_score: 313.8115, mean_absolute_error: 0.1118, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9223, predictive_accuracy: 0.9221, prior_entropy: 0.9982, recall: 0.9221, relative_absolute_error: 0.2241, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2415, root_relative_squared_error: 0.4837, scimark_benchmark: 1322.3407, usercpu_time_millis: 4250, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 4220,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9767, f_measure: 0.9347, kappa: 0.8693, kb_relative_information_score: 329.6642, mean_absolute_error: 0.0898, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9359, predictive_accuracy: 0.9347, prior_entropy: 0.9982, recall: 0.9347, relative_absolute_error: 0.18, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.233, root_relative_squared_error: 0.4665, scimark_benchmark: 1321.8321,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9667, f_measure: 0.8919, kappa: 0.7846, kb_relative_information_score: 310.3361, mean_absolute_error: 0.1099, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.8978, predictive_accuracy: 0.892, prior_entropy: 0.9982, recall: 0.892, relative_absolute_error: 0.2204, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3089, root_relative_squared_error: 0.6187, scimark_benchmark: 1337.1928,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9767, f_measure: 0.9347, kappa: 0.8693, kb_relative_information_score: 329.6642, mean_absolute_error: 0.0898, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9359, predictive_accuracy: 0.9347, prior_entropy: 0.9982, recall: 0.9347, relative_absolute_error: 0.18, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.233, root_relative_squared_error: 0.4665, scimark_benchmark: 1347.6543,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9667, f_measure: 0.8919, kappa: 0.7846, kb_relative_information_score: 310.3361, mean_absolute_error: 0.1099, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.8978, predictive_accuracy: 0.892, prior_entropy: 0.9982, recall: 0.892, relative_absolute_error: 0.2204, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3089, root_relative_squared_error: 0.6187, scimark_benchmark: 1362.9924,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9767, f_measure: 0.9347, kappa: 0.8693, kb_relative_information_score: 329.6642, mean_absolute_error: 0.0898, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9359, predictive_accuracy: 0.9347, prior_entropy: 0.9982, recall: 0.9347, relative_absolute_error: 0.18, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.233, root_relative_squared_error: 0.4665, scimark_benchmark: 1313.8988,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9606, f_measure: 0.9096, kappa: 0.8189, kb_relative_information_score: 276.955, mean_absolute_error: 0.1629, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9101, predictive_accuracy: 0.9095, prior_entropy: 0.9982, recall: 0.9095, relative_absolute_error: 0.3266, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2767, root_relative_squared_error: 0.5541, scimark_benchmark: 1339.2472, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9809, f_measure: 0.9347, kappa: 0.8691, kb_relative_information_score: 315.4704, mean_absolute_error: 0.1108, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9348, predictive_accuracy: 0.9347, prior_entropy: 0.9982, recall: 0.9347, relative_absolute_error: 0.2222, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2332, root_relative_squared_error: 0.467, scimark_benchmark: 1331.7953, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.919, f_measure: 0.9145, kappa: 0.8285, kb_relative_information_score: 314.794, mean_absolute_error: 0.1114, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9148, predictive_accuracy: 0.9146, prior_entropy: 0.9982, recall: 0.9146, relative_absolute_error: 0.2233, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2658, root_relative_squared_error: 0.5322, scimark_benchmark: 1342.8584,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9667, f_measure: 0.8919, kappa: 0.7846, kb_relative_information_score: 310.3361, mean_absolute_error: 0.1099, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.8978, predictive_accuracy: 0.892, prior_entropy: 0.9982, recall: 0.892, relative_absolute_error: 0.2204, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3089, root_relative_squared_error: 0.6187, scimark_benchmark: 1324.7884,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9607, f_measure: 0.912, kappa: 0.8236, kb_relative_information_score: 295.3716, mean_absolute_error: 0.1387, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.912, predictive_accuracy: 0.9121, prior_entropy: 0.9982, recall: 0.9121, relative_absolute_error: 0.2781, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2582, root_relative_squared_error: 0.5171, scimark_benchmark: 1318.4315, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.919, f_measure: 0.9145, kappa: 0.8285, kb_relative_information_score: 314.794, mean_absolute_error: 0.1114, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9148, predictive_accuracy: 0.9146, prior_entropy: 0.9982, recall: 0.9146, relative_absolute_error: 0.2233, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2658, root_relative_squared_error: 0.5322, scimark_benchmark: 1353.0836,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8796, f_measure: 0.8794, kappa: 0.7584, kb_relative_information_score: 301.6456, mean_absolute_error: 0.1206, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.8797, predictive_accuracy: 0.8794, prior_entropy: 0.9982, recall: 0.8794, relative_absolute_error: 0.2418, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3473, root_relative_squared_error: 0.6954, scimark_benchmark: 1533.5367, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9588, f_measure: 0.912, kappa: 0.8235, kb_relative_information_score: 320.5258, mean_absolute_error: 0.0994, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9122, predictive_accuracy: 0.9121, prior_entropy: 0.9982, recall: 0.9121, relative_absolute_error: 0.1992, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.26, root_relative_squared_error: 0.5207, scimark_benchmark: 1077.9216, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9809, f_measure: 0.9347, kappa: 0.8691, kb_relative_information_score: 315.4704, mean_absolute_error: 0.1108, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9348, predictive_accuracy: 0.9347, prior_entropy: 0.9982, recall: 0.9347, relative_absolute_error: 0.2222, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2332, root_relative_squared_error: 0.467, scimark_benchmark: 936.9595, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9782, f_measure: 0.9321, kappa: 0.8639, kb_relative_information_score: 315.4962, mean_absolute_error: 0.1119, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9322, predictive_accuracy: 0.9322, prior_entropy: 0.9982, recall: 0.9322, relative_absolute_error: 0.2245, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2312, root_relative_squared_error: 0.463, scimark_benchmark: 935.5664, usercpu_time_millis: 3220, usercpu_time_millis_testing: 1080, usercpu_time_millis_training: 2140,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9625, f_measure: 0.9171, kappa: 0.8341, kb_relative_information_score: 326.3357, mean_absolute_error: 0.0915, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9181, predictive_accuracy: 0.9171, prior_entropy: 0.9982, recall: 0.9171, relative_absolute_error: 0.1834, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2634, root_relative_squared_error: 0.5275, scimark_benchmark: 941.3057, usercpu_time_millis: 140, usercpu_time_millis_training: 140,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3616, kb_relative_information_score: 18.6258, mean_absolute_error: 0.4749, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.2758, predictive_accuracy: 0.5251, prior_entropy: 0.9982, recall: 0.5251, relative_absolute_error: 0.9521, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.6891, root_relative_squared_error: 1.38, scimark_benchmark: 941.9549,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9363, f_measure: 0.9271, kappa: 0.8539, kb_relative_information_score: 327.3025, mean_absolute_error: 0.0942, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9272, predictive_accuracy: 0.9271, prior_entropy: 0.9982, recall: 0.9271, relative_absolute_error: 0.189, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2497, root_relative_squared_error: 0.5, scimark_benchmark: 942.6192, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9374, f_measure: 0.8793, kappa: 0.7596, kb_relative_information_score: 299.9049, mean_absolute_error: 0.1235, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.8857, predictive_accuracy: 0.8794, prior_entropy: 0.9982, recall: 0.8794, relative_absolute_error: 0.2476, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3422, root_relative_squared_error: 0.6852, scimark_benchmark: 935.6052, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9487, f_measure: 0.8845, kappa: 0.769, kb_relative_information_score: 293.5959, mean_absolute_error: 0.1348, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.8862, predictive_accuracy: 0.8844, prior_entropy: 0.9982, recall: 0.8844, relative_absolute_error: 0.2702, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3011, root_relative_squared_error: 0.6029, scimark_benchmark: 926.5859, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.979, f_measure: 0.9322, kappa: 0.864, kb_relative_information_score: 314.5182, mean_absolute_error: 0.1133, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9322, predictive_accuracy: 0.9322, prior_entropy: 0.9982, recall: 0.9322, relative_absolute_error: 0.2272, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2314, root_relative_squared_error: 0.4633, scimark_benchmark: 945.2015, usercpu_time_millis: 680, usercpu_time_millis_testing: 140, usercpu_time_millis_training: 540,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9791, f_measure: 0.9296, kappa: 0.8589, kb_relative_information_score: 316.1803, mean_absolute_error: 0.1113, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9296, predictive_accuracy: 0.9296, prior_entropy: 0.9982, recall: 0.9296, relative_absolute_error: 0.2232, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2295, root_relative_squared_error: 0.4596, scimark_benchmark: 938.988, usercpu_time_millis: 1290, usercpu_time_millis_testing: 250, usercpu_time_millis_training: 1040,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9763, f_measure: 0.9221, kappa: 0.844, kb_relative_information_score: 313.5849, mean_absolute_error: 0.1138, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9225, predictive_accuracy: 0.9221, prior_entropy: 0.9982, recall: 0.9221, relative_absolute_error: 0.2282, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.235, root_relative_squared_error: 0.4706, scimark_benchmark: 932.4744, usercpu_time_millis: 310, usercpu_time_millis_testing: 60, usercpu_time_millis_training: 250,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9677, f_measure: 0.9372, kappa: 0.8741, kb_relative_information_score: 318.2846, mean_absolute_error: 0.1077, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9373, predictive_accuracy: 0.9372, prior_entropy: 0.9982, recall: 0.9372, relative_absolute_error: 0.216, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2321, root_relative_squared_error: 0.4649, scimark_benchmark: 936.7184, usercpu_time_millis: 190, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 150,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6008, f_measure: 0.547, kappa: 0.2095, kb_relative_information_score: 94.9007, mean_absolute_error: 0.3794, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.7681, predictive_accuracy: 0.6206, prior_entropy: 0.9982, recall: 0.6206, relative_absolute_error: 0.7607, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.616, root_relative_squared_error: 1.2335, scimark_benchmark: 934.5964, usercpu_time_millis: 60, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9767, f_measure: 0.9347, kappa: 0.8693, kb_relative_information_score: 329.6642, mean_absolute_error: 0.0898, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9359, predictive_accuracy: 0.9347, prior_entropy: 0.9982, recall: 0.9347, relative_absolute_error: 0.18, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.233, root_relative_squared_error: 0.4665, scimark_benchmark: 930.404, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9767, f_measure: 0.9347, kappa: 0.8693, kb_relative_information_score: 329.6642, mean_absolute_error: 0.0898, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9359, predictive_accuracy: 0.9347, prior_entropy: 0.9982, recall: 0.9347, relative_absolute_error: 0.18, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.233, root_relative_squared_error: 0.4665, scimark_benchmark: 930.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6008, f_measure: 0.547, kappa: 0.2095, kb_relative_information_score: 94.9007, mean_absolute_error: 0.3794, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.7681, predictive_accuracy: 0.6206, prior_entropy: 0.9982, recall: 0.6206, relative_absolute_error: 0.7607, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.616, root_relative_squared_error: 1.2335, scimark_benchmark: 937.5683, usercpu_time_millis: 50, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9606, f_measure: 0.9096, kappa: 0.8189, kb_relative_information_score: 276.955, mean_absolute_error: 0.1629, mean_prior_absolute_error: 0.4987, number_of_instances: 398, precision: 0.9101, predictive_accuracy: 0.9095, prior_entropy: 0.9982, recall: 0.9095, relative_absolute_error: 0.3266, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.2767, root_relative_squared_error: 0.5541, scimark_benchmark: 901.6243, usercpu_time_millis: 10, usercpu_time_millis_training: 10,

Metric:

Timeline

Plotting contribution timeline

Leaderboard

Rank Name Top Score Entries Highest rank

Note: The leaderboard ignores resubmissions of previous solutions, as well as parameter variations that do not improve performance.

Challenge

In supervised classification, you are given an input dataset in which instances are labeled with a certain class. The goal is to build a model that predicts the class for future unlabeled instances. The model is evaluated using a train-test procedure, e.g. cross-validation.

To make results by different users comparable, you are given the exact train-test folds to be used, and you need to return at least the predictions generated by your model for each of the test instances. OpenML will use these predictions to calculate a range of evaluation measures on the server.

You can also upload your own evaluation measures, provided that the code for doing so is available from the implementation used. For extremely large datasets, it may be infeasible to upload all predictions. In those cases, you need to compute and provide the evaluations yourself.

Optionally, you can upload the model trained on all the input data. There is no restriction on the file format, but please use a well-known format or PMML.

Given inputs

Expected outputs

evaluations A list of user-defined evaluations of the task as key-value pairs. KeyValue (optional)
model A file containing the model built on all the input data. File (optional)
predictions The desired output format Predictions (optional)

How to submit runs

Using your favorite machine learning environment

Download this task directly in your environment and automatically upload your results

OpenML bootcamp

From your own software

Use one of our APIs to download data from OpenML and upload your results

OpenML APIs