OpenML
Supervised Classification on confidence

Supervised Classification on confidence

Task 3559 Supervised Classification confidence 374 runs submitted
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  • study_1 study_107 study_123 study_41 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7611, f_measure: 0.2, kappa: 0.1333, kb_relative_information_score: 27.4752, mean_absolute_error: 0.2232, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.1786, predictive_accuracy: 0.2778, prior_entropy: 2.585, recall: 0.2778, relative_absolute_error: 0.8035, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.3349, root_relative_squared_error: 0.8986, scimark_benchmark: 912.7324,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9549, f_measure: 0.777, kappa: 0.75, kb_relative_information_score: 53.8779, mean_absolute_error: 0.0989, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.7746, predictive_accuracy: 0.7917, prior_entropy: 2.585, recall: 0.7917, relative_absolute_error: 0.3559, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.2165, root_relative_squared_error: 0.581, scimark_benchmark: 942.6843,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.952, f_measure: 0.7933, kappa: 0.75, kb_relative_information_score: 56.2388, mean_absolute_error: 0.0696, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.7993, predictive_accuracy: 0.7917, prior_entropy: 2.585, recall: 0.7917, relative_absolute_error: 0.2506, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.2443, root_relative_squared_error: 0.6555, scimark_benchmark: 937.1527, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9667, f_measure: 0.8298, kappa: 0.8, kb_relative_information_score: 55.9189, mean_absolute_error: 0.0888, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.8286, predictive_accuracy: 0.8333, prior_entropy: 2.585, recall: 0.8333, relative_absolute_error: 0.3196, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.205, root_relative_squared_error: 0.55, scimark_benchmark: 940.0008,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9669, f_measure: 0.8014, kappa: 0.7667, kb_relative_information_score: 55.6318, mean_absolute_error: 0.0904, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.8007, predictive_accuracy: 0.8056, prior_entropy: 2.585, recall: 0.8056, relative_absolute_error: 0.3253, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.2082, root_relative_squared_error: 0.5586, scimark_benchmark: 938.0414,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8742, f_measure: 0.7777, kappa: 0.7333, kb_relative_information_score: 53.3753, mean_absolute_error: 0.0818, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.7823, predictive_accuracy: 0.7778, prior_entropy: 2.585, recall: 0.7778, relative_absolute_error: 0.2946, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.2691, root_relative_squared_error: 0.722, scimark_benchmark: 1321.9426,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7611, f_measure: 0.2, kappa: 0.1333, kb_relative_information_score: 27.4752, mean_absolute_error: 0.2232, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.1786, predictive_accuracy: 0.2778, prior_entropy: 2.585, recall: 0.2778, relative_absolute_error: 0.8035, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.3349, root_relative_squared_error: 0.8986, scimark_benchmark: 930.5999,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7611, f_measure: 0.2, kappa: 0.1333, kb_relative_information_score: 27.4752, mean_absolute_error: 0.2232, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.1786, predictive_accuracy: 0.2778, prior_entropy: 2.585, recall: 0.2778, relative_absolute_error: 0.8035, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.3349, root_relative_squared_error: 0.8986, scimark_benchmark: 916.6405,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7611, f_measure: 0.2, kappa: 0.1333, kb_relative_information_score: 27.4752, mean_absolute_error: 0.2232, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.1786, predictive_accuracy: 0.2778, prior_entropy: 2.585, recall: 0.2778, relative_absolute_error: 0.8035, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.3349, root_relative_squared_error: 0.8986, scimark_benchmark: 1336.2509,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7611, f_measure: 0.2, kappa: 0.1333, kb_relative_information_score: 27.4752, mean_absolute_error: 0.2232, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.1786, predictive_accuracy: 0.2778, prior_entropy: 2.585, recall: 0.2778, relative_absolute_error: 0.8035, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.3349, root_relative_squared_error: 0.8986, scimark_benchmark: 1404.1865, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7611, f_measure: 0.2, kappa: 0.1333, kb_relative_information_score: 27.4752, mean_absolute_error: 0.2232, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.1786, predictive_accuracy: 0.2778, prior_entropy: 2.585, recall: 0.2778, relative_absolute_error: 0.8035, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.3349, root_relative_squared_error: 0.8986, scimark_benchmark: 933.3136,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9655, f_measure: 0.8837, kappa: 0.8667, kb_relative_information_score: 60.2806, mean_absolute_error: 0.0614, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.8935, predictive_accuracy: 0.8889, prior_entropy: 2.585, recall: 0.8889, relative_absolute_error: 0.2211, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.1856, root_relative_squared_error: 0.4981, scimark_benchmark: 916.6405,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9424, f_measure: 0.8177, kappa: 0.7833, kb_relative_information_score: 58.9286, mean_absolute_error: 0.0682, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.8236, predictive_accuracy: 0.8194, prior_entropy: 2.585, recall: 0.8194, relative_absolute_error: 0.2455, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.204, root_relative_squared_error: 0.5474, scimark_benchmark: 825.5282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6697, f_measure: 0.5502, kappa: 0.45, kb_relative_information_score: 15.314, mean_absolute_error: 0.2596, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.5923, predictive_accuracy: 0.5417, prior_entropy: 2.585, recall: 0.5417, relative_absolute_error: 0.9344, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.3655, root_relative_squared_error: 0.9809, scimark_benchmark: 887.6719, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.901, f_measure: 0.6029, kappa: 0.5333, kb_relative_information_score: 23.2424, mean_absolute_error: 0.233, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.6232, predictive_accuracy: 0.6111, prior_entropy: 2.585, recall: 0.6111, relative_absolute_error: 0.8389, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.3272, root_relative_squared_error: 0.878, scimark_benchmark: 933.3136, usercpu_time_millis: 60, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.953, f_measure: 0.8282, kappa: 0.8, kb_relative_information_score: 51.3834, mean_absolute_error: 0.1091, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.8314, predictive_accuracy: 0.8333, prior_entropy: 2.585, recall: 0.8333, relative_absolute_error: 0.3928, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.2368, root_relative_squared_error: 0.6354, scimark_benchmark: 938.343, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7333, f_measure: 0.5403, kappa: 0.4667, kb_relative_information_score: 36.7438, mean_absolute_error: 0.1481, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.5785, predictive_accuracy: 0.5556, prior_entropy: 2.585, recall: 0.5556, relative_absolute_error: 0.5333, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.3849, root_relative_squared_error: 1.0328, scimark_benchmark: 1304.9611, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9563, f_measure: 0.7812, kappa: 0.75, kb_relative_information_score: 55.6135, mean_absolute_error: 0.0826, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.7906, predictive_accuracy: 0.7917, prior_entropy: 2.585, recall: 0.7917, relative_absolute_error: 0.2973, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.225, root_relative_squared_error: 0.6038, scimark_benchmark: 1337.7959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9308, f_measure: 0.7483, kappa: 0.7167, kb_relative_information_score: 50.2136, mean_absolute_error: 0.1123, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.7654, predictive_accuracy: 0.7639, prior_entropy: 2.585, recall: 0.7639, relative_absolute_error: 0.4044, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.241, root_relative_squared_error: 0.6466, scimark_benchmark: 1319.6463, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9711, f_measure: 0.8362, kappa: 0.8, kb_relative_information_score: 56.5954, mean_absolute_error: 0.081, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.8425, predictive_accuracy: 0.8333, prior_entropy: 2.585, recall: 0.8333, relative_absolute_error: 0.2915, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.2087, root_relative_squared_error: 0.5601, scimark_benchmark: 1280.6952,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8667, f_measure: 0.7772, kappa: 0.7333, kb_relative_information_score: 54.3719, mean_absolute_error: 0.0741, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.7776, predictive_accuracy: 0.7778, prior_entropy: 2.585, recall: 0.7778, relative_absolute_error: 0.2667, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.2722, root_relative_squared_error: 0.7303, scimark_benchmark: 1346.9602,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9133, f_measure: 0.7778, kappa: 0.75, kb_relative_information_score: 53.8906, mean_absolute_error: 0.0883, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.8076, predictive_accuracy: 0.7917, prior_entropy: 2.585, recall: 0.7917, relative_absolute_error: 0.3179, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.2393, root_relative_squared_error: 0.6421, scimark_benchmark: 1319.9043,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9017, f_measure: 0.796, kappa: 0.7667, kb_relative_information_score: 54.8379, mean_absolute_error: 0.0803, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.8054, predictive_accuracy: 0.8056, prior_entropy: 2.585, recall: 0.8056, relative_absolute_error: 0.2891, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.2432, root_relative_squared_error: 0.6526, scimark_benchmark: 1309.3173,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8583, f_measure: 0.7629, kappa: 0.7167, kb_relative_information_score: 53.2702, mean_absolute_error: 0.0787, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.7723, predictive_accuracy: 0.7639, prior_entropy: 2.585, recall: 0.7639, relative_absolute_error: 0.2833, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.2805, root_relative_squared_error: 0.7528, scimark_benchmark: 825.5282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9471, f_measure: 0.8204, kappa: 0.7833, kb_relative_information_score: 57.6975, mean_absolute_error: 0.06, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.8231, predictive_accuracy: 0.8194, prior_entropy: 2.585, recall: 0.8194, relative_absolute_error: 0.2161, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.2445, root_relative_squared_error: 0.656, scimark_benchmark: 868.2731, usercpu_time_millis: 1170, usercpu_time_millis_training: 1170,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5583, f_measure: 0.215, kappa: 0.1167, kb_relative_information_score: 13.607, mean_absolute_error: 0.2454, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.3088, predictive_accuracy: 0.2639, prior_entropy: 2.585, recall: 0.2639, relative_absolute_error: 0.8833, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.4953, root_relative_squared_error: 1.3292, scimark_benchmark: 1339.4189,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8788, f_measure: 0.7674, kappa: 0.7167, kb_relative_information_score: 52.4057, mean_absolute_error: 0.0867, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.7855, predictive_accuracy: 0.7639, prior_entropy: 2.585, recall: 0.7639, relative_absolute_error: 0.3122, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.2731, root_relative_squared_error: 0.7327, scimark_benchmark: 1339.4189,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8167, f_measure: 0.6966, kappa: 0.6333, kb_relative_information_score: 47.7614, mean_absolute_error: 0.1019, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.7039, predictive_accuracy: 0.6944, prior_entropy: 2.585, recall: 0.6944, relative_absolute_error: 0.3667, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.3191, root_relative_squared_error: 0.8563, scimark_benchmark: 1351.788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8333, f_measure: 0.7165, kappa: 0.6667, kb_relative_information_score: 49.9649, mean_absolute_error: 0.0926, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.7194, predictive_accuracy: 0.7222, prior_entropy: 2.585, recall: 0.7222, relative_absolute_error: 0.3333, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.3043, root_relative_squared_error: 0.8165, scimark_benchmark: 1505.597,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4167, f_measure: 0.0637, kappa: -0.0333, kb_relative_information_score: 0.2624, mean_absolute_error: 0.2784, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.0468, predictive_accuracy: 0.1389, prior_entropy: 2.585, recall: 0.1389, relative_absolute_error: 1.0022, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.3735, root_relative_squared_error: 1.0023, scimark_benchmark: 1505.597,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8742, f_measure: 0.7777, kappa: 0.7333, kb_relative_information_score: 53.3753, mean_absolute_error: 0.0818, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.7823, predictive_accuracy: 0.7778, prior_entropy: 2.585, recall: 0.7778, relative_absolute_error: 0.2946, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.2691, root_relative_squared_error: 0.722, scimark_benchmark: 1384.4418,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8856, f_measure: 0.8204, kappa: 0.7833, kb_relative_information_score: 57.5853, mean_absolute_error: 0.0642, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.8256, predictive_accuracy: 0.8194, prior_entropy: 2.585, recall: 0.8194, relative_absolute_error: 0.2312, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.2363, root_relative_squared_error: 0.634, scimark_benchmark: 942.6953, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8752, f_measure: 0.8204, kappa: 0.7833, kb_relative_information_score: 57.054, mean_absolute_error: 0.0659, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.8256, predictive_accuracy: 0.8194, prior_entropy: 2.585, recall: 0.8194, relative_absolute_error: 0.2372, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.242, root_relative_squared_error: 0.6493, scimark_benchmark: 926.6717, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.872, f_measure: 0.8204, kappa: 0.7833, kb_relative_information_score: 57.0539, mean_absolute_error: 0.0659, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.8256, predictive_accuracy: 0.8194, prior_entropy: 2.585, recall: 0.8194, relative_absolute_error: 0.2372, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.242, root_relative_squared_error: 0.6493, scimark_benchmark: 936.7115, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7611, f_measure: 0.2, kappa: 0.1333, kb_relative_information_score: 27.4752, mean_absolute_error: 0.2232, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.1786, predictive_accuracy: 0.2778, prior_entropy: 2.585, recall: 0.2778, relative_absolute_error: 0.8035, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.3349, root_relative_squared_error: 0.8986, scimark_benchmark: 894.7455,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7611, f_measure: 0.2, kappa: 0.1333, kb_relative_information_score: 27.4752, mean_absolute_error: 0.2232, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.1786, predictive_accuracy: 0.2778, prior_entropy: 2.585, recall: 0.2778, relative_absolute_error: 0.8035, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.3349, root_relative_squared_error: 0.8986, scimark_benchmark: 936.6206,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7611, f_measure: 0.2, kappa: 0.1333, kb_relative_information_score: 27.4752, mean_absolute_error: 0.2232, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.1786, predictive_accuracy: 0.2778, prior_entropy: 2.585, recall: 0.2778, relative_absolute_error: 0.8035, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.3349, root_relative_squared_error: 0.8986, scimark_benchmark: 911.3823,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7611, f_measure: 0.2, kappa: 0.1333, kb_relative_information_score: 27.4752, mean_absolute_error: 0.2232, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.1786, predictive_accuracy: 0.2778, prior_entropy: 2.585, recall: 0.2778, relative_absolute_error: 0.8035, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.3349, root_relative_squared_error: 0.8986, scimark_benchmark: 933.8635,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7611, f_measure: 0.2, kappa: 0.1333, kb_relative_information_score: 27.4752, mean_absolute_error: 0.2232, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.1786, predictive_accuracy: 0.2778, prior_entropy: 2.585, recall: 0.2778, relative_absolute_error: 0.8035, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.3349, root_relative_squared_error: 0.8986, scimark_benchmark: 938.9865,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8993, f_measure: 0.7816, kappa: 0.7333, kb_relative_information_score: 54.8039, mean_absolute_error: 0.0727, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.7904, predictive_accuracy: 0.7778, prior_entropy: 2.585, recall: 0.7778, relative_absolute_error: 0.2616, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.2672, root_relative_squared_error: 0.717, scimark_benchmark: 945.6434, usercpu_time_millis: 90, usercpu_time_millis_training: 90,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9413, build_cpu_time: 0.8991, build_memory: 1862160758.3333, f_measure: 0.8509, kappa: 0.8167, kb_relative_information_score: 60.0963, mean_absolute_error: 0.0517, mean_prior_absolute_error: 0.2778, number_of_instances: 72, precision: 0.8733, predictive_accuracy: 0.8472, prior_entropy: 2.585, recall: 0.8472, relative_absolute_error: 0.186, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.2188, root_relative_squared_error: 0.5871, scimark_benchmark: 916.8903,
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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