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OpenML
OpenML
Supervised Classification on sleuth_case1202

Supervised Classification on sleuth_case1202

Task 3754 Supervised Classification sleuth_case1202 512 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • mythbusting_1 study_1 study_107 study_15 study_20 study_41 under100k under1m
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512 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8219, f_measure: 0.7634, kappa: 0.5015, kb_relative_information_score: 37.4447, mean_absolute_error: 0.2849, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.7634, predictive_accuracy: 0.7634, prior_entropy: 0.9645, recall: 0.7634, relative_absolute_error: 0.5997, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.4012, root_relative_squared_error: 0.8237, scimark_benchmark: 942.9518,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8216, f_measure: 0.8089, kappa: 0.612, kb_relative_information_score: 54.1758, mean_absolute_error: 0.1935, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.83, predictive_accuracy: 0.8065, prior_entropy: 0.9645, recall: 0.8065, relative_absolute_error: 0.4074, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.4399, root_relative_squared_error: 0.9032, scimark_benchmark: 1336.3256,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4658, kb_relative_information_score: 15.5003, mean_absolute_error: 0.3871, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.3757, predictive_accuracy: 0.6129, prior_entropy: 0.9645, recall: 0.6129, relative_absolute_error: 0.8149, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.6222, root_relative_squared_error: 1.2773, scimark_benchmark: 1333.5799, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7646, f_measure: 0.7747, kappa: 0.5265, kb_relative_information_score: 47.7299, mean_absolute_error: 0.2258, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.7755, predictive_accuracy: 0.7742, prior_entropy: 0.9645, recall: 0.7742, relative_absolute_error: 0.4753, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.4752, root_relative_squared_error: 0.9756, scimark_benchmark: 1297.6599,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9001, f_measure: 0.8176, kappa: 0.6167, kb_relative_information_score: 43.0824, mean_absolute_error: 0.2672, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.8183, predictive_accuracy: 0.8172, prior_entropy: 0.9645, recall: 0.8172, relative_absolute_error: 0.5624, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.3577, root_relative_squared_error: 0.7343, scimark_benchmark: 938.343, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6667, f_measure: 0.6705, kappa: 0.3218, kb_relative_information_score: 26.2435, mean_absolute_error: 0.3333, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.6819, predictive_accuracy: 0.6667, prior_entropy: 0.9645, recall: 0.6667, relative_absolute_error: 0.7017, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.5774, root_relative_squared_error: 1.1853, scimark_benchmark: 940.3347, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8962, f_measure: 0.8167, kappa: 0.6128, kb_relative_information_score: 45.3327, mean_absolute_error: 0.2546, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.8164, predictive_accuracy: 0.8172, prior_entropy: 0.9645, recall: 0.8172, relative_absolute_error: 0.5359, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.3583, root_relative_squared_error: 0.7355, scimark_benchmark: 934.4732, usercpu_time_millis: 80, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4658, kb_relative_information_score: 15.5003, mean_absolute_error: 0.3871, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.3757, predictive_accuracy: 0.6129, prior_entropy: 0.9645, recall: 0.6129, relative_absolute_error: 0.8149, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.6222, root_relative_squared_error: 1.2773, scimark_benchmark: 918.6491, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8056, f_measure: 0.8408, kappa: 0.6782, kb_relative_information_score: 49.1103, mean_absolute_error: 0.2332, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.8663, predictive_accuracy: 0.8387, prior_entropy: 0.9645, recall: 0.8387, relative_absolute_error: 0.4909, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.3693, root_relative_squared_error: 0.7581, scimark_benchmark: 918.6491,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8382, f_measure: 0.8514, kappa: 0.7011, kb_relative_information_score: 48.7237, mean_absolute_error: 0.2345, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.8815, predictive_accuracy: 0.8495, prior_entropy: 0.9645, recall: 0.8495, relative_absolute_error: 0.4936, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.3547, root_relative_squared_error: 0.7281, scimark_benchmark: 1368.9272,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8212, f_measure: 0.8514, kappa: 0.7011, kb_relative_information_score: 48.9402, mean_absolute_error: 0.2341, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.8815, predictive_accuracy: 0.8495, prior_entropy: 0.9645, recall: 0.8495, relative_absolute_error: 0.4927, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.358, root_relative_squared_error: 0.7349, scimark_benchmark: 1028.5889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8572, f_measure: 0.8408, kappa: 0.6751, kb_relative_information_score: 49.6117, mean_absolute_error: 0.2308, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.8585, predictive_accuracy: 0.8387, prior_entropy: 0.9645, recall: 0.8387, relative_absolute_error: 0.4859, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.3609, root_relative_squared_error: 0.7409, scimark_benchmark: 938.5465, usercpu_time_millis: 110, usercpu_time_millis_training: 110,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8465, f_measure: 0.8406, kappa: 0.6718, kb_relative_information_score: 44.4279, mean_absolute_error: 0.2564, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.8519, predictive_accuracy: 0.8387, prior_entropy: 0.9645, recall: 0.8387, relative_absolute_error: 0.5398, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.3766, root_relative_squared_error: 0.7732, scimark_benchmark: 1327.8711, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7493, f_measure: 0.7705, kappa: 0.5116, kb_relative_information_score: 47.7299, mean_absolute_error: 0.2258, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.7716, predictive_accuracy: 0.7742, prior_entropy: 0.9645, recall: 0.7742, relative_absolute_error: 0.4753, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.4752, root_relative_squared_error: 0.9756, scimark_benchmark: 1315.0767,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.816, f_measure: 0.8407, kappa: 0.6813, kb_relative_information_score: 50.6051, mean_absolute_error: 0.2229, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.8755, predictive_accuracy: 0.8387, prior_entropy: 0.9645, recall: 0.8387, relative_absolute_error: 0.4693, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.3471, root_relative_squared_error: 0.7126, scimark_benchmark: 1306.6379,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8287, f_measure: 0.8514, kappa: 0.7011, kb_relative_information_score: 52.3892, mean_absolute_error: 0.2145, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.8815, predictive_accuracy: 0.8495, prior_entropy: 0.9645, recall: 0.8495, relative_absolute_error: 0.4516, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.3391, root_relative_squared_error: 0.6961, scimark_benchmark: 1290.1085,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7544, f_measure: 0.7722, kappa: 0.5167, kb_relative_information_score: 47.7299, mean_absolute_error: 0.2258, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.7718, predictive_accuracy: 0.7742, prior_entropy: 0.9645, recall: 0.7742, relative_absolute_error: 0.4753, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.4752, root_relative_squared_error: 0.9756, scimark_benchmark: 1341.5768,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6404, f_measure: 0.6725, kappa: 0.3145, kb_relative_information_score: 34.838, mean_absolute_error: 0.2903, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.734, predictive_accuracy: 0.7097, prior_entropy: 0.9645, recall: 0.7097, relative_absolute_error: 0.6112, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.5388, root_relative_squared_error: 1.1062, scimark_benchmark: 1280.6952,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7629, f_measure: 0.744, kappa: 0.467, kb_relative_information_score: 38.6157, mean_absolute_error: 0.2729, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.7489, predictive_accuracy: 0.7419, prior_entropy: 0.9645, recall: 0.7419, relative_absolute_error: 0.5744, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.4724, root_relative_squared_error: 0.9698, scimark_benchmark: 1392.1129,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8582, f_measure: 0.8408, kappa: 0.6782, kb_relative_information_score: 60.6217, mean_absolute_error: 0.1613, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.8663, predictive_accuracy: 0.8387, prior_entropy: 0.9645, recall: 0.8387, relative_absolute_error: 0.3395, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.4016, root_relative_squared_error: 0.8245, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7822, f_measure: 0.7951, kappa: 0.5672, kb_relative_information_score: 52.0272, mean_absolute_error: 0.2043, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.7948, predictive_accuracy: 0.7957, prior_entropy: 0.9645, recall: 0.7957, relative_absolute_error: 0.4301, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.452, root_relative_squared_error: 0.928, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4474, f_measure: 0.4658, kb_relative_information_score: -0.2085, mean_absolute_error: 0.4755, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.3757, predictive_accuracy: 0.6129, prior_entropy: 0.9645, recall: 0.6129, relative_absolute_error: 1.001, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.4876, root_relative_squared_error: 1.001, scimark_benchmark: 1330.0803,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8285, f_measure: 0.8407, kappa: 0.6813, kb_relative_information_score: 51.2842, mean_absolute_error: 0.2192, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.8755, predictive_accuracy: 0.8387, prior_entropy: 0.9645, recall: 0.8387, relative_absolute_error: 0.4614, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.3482, root_relative_squared_error: 0.7149, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8981, f_measure: 0.8176, kappa: 0.6167, kb_relative_information_score: 57.276, mean_absolute_error: 0.1795, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.8183, predictive_accuracy: 0.8172, prior_entropy: 0.9645, recall: 0.8172, relative_absolute_error: 0.3778, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.4067, root_relative_squared_error: 0.8349, scimark_benchmark: 927.0753, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8621, f_measure: 0.8073, kappa: 0.5962, kb_relative_information_score: 51.3189, mean_absolute_error: 0.2121, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.809, predictive_accuracy: 0.8065, prior_entropy: 0.9645, recall: 0.8065, relative_absolute_error: 0.4465, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.3985, root_relative_squared_error: 0.8181, scimark_benchmark: 941.7954, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9006, f_measure: 0.8287, kappa: 0.6411, kb_relative_information_score: 52.7473, mean_absolute_error: 0.2052, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.8303, predictive_accuracy: 0.828, prior_entropy: 0.9645, recall: 0.828, relative_absolute_error: 0.4319, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.3703, root_relative_squared_error: 0.7602, scimark_benchmark: 923.7642, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9006, f_measure: 0.8287, kappa: 0.6411, kb_relative_information_score: 52.7473, mean_absolute_error: 0.2052, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.8303, predictive_accuracy: 0.828, prior_entropy: 0.9645, recall: 0.828, relative_absolute_error: 0.4319, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.3703, root_relative_squared_error: 0.7602, scimark_benchmark: 894.7455, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8631, f_measure: 0.8298, kappa: 0.6482, kb_relative_information_score: 57.24, mean_absolute_error: 0.1802, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.8385, predictive_accuracy: 0.828, prior_entropy: 0.9645, recall: 0.828, relative_absolute_error: 0.3792, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.4042, root_relative_squared_error: 0.8298, scimark_benchmark: 940.2922, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8653, f_measure: 0.8406, kappa: 0.6718, kb_relative_information_score: 59.7123, mean_absolute_error: 0.1671, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.8519, predictive_accuracy: 0.8387, prior_entropy: 0.9645, recall: 0.8387, relative_absolute_error: 0.3518, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.3855, root_relative_squared_error: 0.7914, scimark_benchmark: 938.2848, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8655, f_measure: 0.8408, kappa: 0.6782, kb_relative_information_score: 60.8273, mean_absolute_error: 0.1619, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.8663, predictive_accuracy: 0.8387, prior_entropy: 0.9645, recall: 0.8387, relative_absolute_error: 0.3408, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.3802, root_relative_squared_error: 0.7805, scimark_benchmark: 936.6206, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8462, f_measure: 0.8195, kappa: 0.6317, kb_relative_information_score: 53.9484, mean_absolute_error: 0.197, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.8371, predictive_accuracy: 0.8172, prior_entropy: 0.9645, recall: 0.8172, relative_absolute_error: 0.4147, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.403, root_relative_squared_error: 0.8273, scimark_benchmark: 922.9039, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8543, f_measure: 0.8514, kappa: 0.7011, kb_relative_information_score: 61.9001, mean_absolute_error: 0.1559, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.8815, predictive_accuracy: 0.8495, prior_entropy: 0.9645, recall: 0.8495, relative_absolute_error: 0.3282, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.3886, root_relative_squared_error: 0.7978, scimark_benchmark: 938.9865,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8587, f_measure: 0.8065, kappa: 0.5921, kb_relative_information_score: 52.9959, mean_absolute_error: 0.2005, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.8065, predictive_accuracy: 0.8065, prior_entropy: 0.9645, recall: 0.8065, relative_absolute_error: 0.4221, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.4176, root_relative_squared_error: 0.8573, scimark_benchmark: 938.4285, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8684, f_measure: 0.827, kappa: 0.6337, kb_relative_information_score: 53.2698, mean_absolute_error: 0.2035, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.8268, predictive_accuracy: 0.828, prior_entropy: 0.9645, recall: 0.828, relative_absolute_error: 0.4284, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.401, root_relative_squared_error: 0.8232, scimark_benchmark: 924.6116, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.867, f_measure: 0.828, kappa: 0.6374, kb_relative_information_score: 51.5389, mean_absolute_error: 0.2124, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.828, predictive_accuracy: 0.828, prior_entropy: 0.9645, recall: 0.828, relative_absolute_error: 0.4471, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.3862, root_relative_squared_error: 0.7928, scimark_benchmark: 924.6116, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8618, build_cpu_time: 0.5507, build_memory: 28458195.5269, f_measure: 0.7837, kappa: 0.5421, kb_relative_information_score: 49.8346, mean_absolute_error: 0.2145, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.7833, predictive_accuracy: 0.7849, prior_entropy: 0.9645, recall: 0.7849, relative_absolute_error: 0.4515, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.4417, root_relative_squared_error: 0.9069, scimark_benchmark: 939.521,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8852, build_cpu_time: 0.3384, build_memory: 303227583.3118, f_measure: 0.7951, kappa: 0.5672, kb_relative_information_score: 54.6227, mean_absolute_error: 0.1911, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.7948, predictive_accuracy: 0.7957, prior_entropy: 0.9645, recall: 0.7957, relative_absolute_error: 0.4023, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.4092, root_relative_squared_error: 0.84, scimark_benchmark: 923.9118,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8319, build_cpu_time: 0.0919, build_memory: 1325856315.0968, f_measure: 0.8073, kappa: 0.5962, kb_relative_information_score: 52.9196, mean_absolute_error: 0.2004, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.809, predictive_accuracy: 0.8065, prior_entropy: 0.9645, recall: 0.8065, relative_absolute_error: 0.4218, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.4394, root_relative_squared_error: 0.902, scimark_benchmark: 874.7324,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8385, build_cpu_time: 0.3074, build_memory: 761934378.4086, f_measure: 0.8176, kappa: 0.6167, kb_relative_information_score: 55.5348, mean_absolute_error: 0.1877, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.8183, predictive_accuracy: 0.8172, prior_entropy: 0.9645, recall: 0.8172, relative_absolute_error: 0.3951, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.4286, root_relative_squared_error: 0.8798, scimark_benchmark: 945.0532,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.875, build_cpu_time: 0.0112, build_memory: 837334313.8065, f_measure: 0.7343, kappa: 0.4329, kb_relative_information_score: 46.246, mean_absolute_error: 0.2322, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.7385, predictive_accuracy: 0.7419, prior_entropy: 0.9645, recall: 0.7419, relative_absolute_error: 0.4887, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.4335, root_relative_squared_error: 0.89, scimark_benchmark: 945.0554,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.875, build_cpu_time: 0.0106, build_memory: 321207121.3763, f_measure: 0.7343, kappa: 0.4329, kb_relative_information_score: 46.246, mean_absolute_error: 0.2322, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.7385, predictive_accuracy: 0.7419, prior_entropy: 0.9645, recall: 0.7419, relative_absolute_error: 0.4887, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.4335, root_relative_squared_error: 0.89, scimark_benchmark: 890.3066,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.875, build_cpu_time: 0.0096, build_memory: 894666394.7527, f_measure: 0.7343, kappa: 0.4329, kb_relative_information_score: 46.246, mean_absolute_error: 0.2322, mean_prior_absolute_error: 0.475, number_of_instances: 93, precision: 0.7385, predictive_accuracy: 0.7419, prior_entropy: 0.9645, recall: 0.7419, relative_absolute_error: 0.4887, root_mean_prior_squared_error: 0.4871, root_mean_squared_error: 0.4335, root_relative_squared_error: 0.89, scimark_benchmark: 943.4039,

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