OpenML
Supervised Classification on BNG(tic-tac-toe)

Supervised Classification on BNG(tic-tac-toe)

Task 1856 Supervised Classification BNG(tic-tac-toe) 238 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7598, f_measure: 0.7165, kappa: 0.3608, kb_relative_information_score: 40324.3374, mean_absolute_error: 0.3651, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7184, predictive_accuracy: 0.7283, prior_entropy: 0.9315, recall: 0.7283, relative_absolute_error: 0.8055, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.4278, root_relative_squared_error: 0.8986, scimark_benchmark: 942.6843, usercpu_time_millis: 3450, usercpu_time_millis_testing: 160, usercpu_time_millis_training: 3290,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7598, f_measure: 0.7166, kappa: 0.361, kb_relative_information_score: 40365.2623, mean_absolute_error: 0.365, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7185, predictive_accuracy: 0.7284, prior_entropy: 0.9315, recall: 0.7284, relative_absolute_error: 0.8053, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.4278, root_relative_squared_error: 0.8986, scimark_benchmark: 935.5075, usercpu_time_millis: 1650, usercpu_time_millis_testing: 90, usercpu_time_millis_training: 1560,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7595, f_measure: 0.7169, kappa: 0.3619, kb_relative_information_score: 40547.9892, mean_absolute_error: 0.3646, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7186, predictive_accuracy: 0.7285, prior_entropy: 0.9315, recall: 0.7285, relative_absolute_error: 0.8044, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.4278, root_relative_squared_error: 0.8987, scimark_benchmark: 939.5088, usercpu_time_millis: 750, usercpu_time_millis_testing: 60, usercpu_time_millis_training: 690,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7551, f_measure: 0.7104, kappa: 0.3466, kb_relative_information_score: 40477.7498, mean_absolute_error: 0.3644, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7134, predictive_accuracy: 0.724, prior_entropy: 0.9315, recall: 0.724, relative_absolute_error: 0.8041, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.4294, root_relative_squared_error: 0.902, scimark_benchmark: 915.9324, usercpu_time_millis: 450, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 410,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8539, f_measure: 0.7889, kappa: 0.5286, kb_relative_information_score: 73803.178, mean_absolute_error: 0.2893, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7885, predictive_accuracy: 0.7924, prior_entropy: 0.9315, recall: 0.7924, relative_absolute_error: 0.6382, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.3811, root_relative_squared_error: 0.8006, scimark_benchmark: 1442.7264, usercpu_time_millis: 123290, usercpu_time_millis_testing: 123280, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8457, f_measure: 0.7863, kappa: 0.5244, kb_relative_information_score: 76642.1294, mean_absolute_error: 0.2802, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7854, predictive_accuracy: 0.7886, prior_entropy: 0.9315, recall: 0.7886, relative_absolute_error: 0.6181, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.3868, root_relative_squared_error: 0.8125, scimark_benchmark: 1363.454, usercpu_time_millis: 100240, usercpu_time_millis_testing: 100240,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6033, f_measure: 0.6536, kappa: 0.2195, kb_relative_information_score: 46163.383, mean_absolute_error: 0.3329, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.6506, predictive_accuracy: 0.6671, prior_entropy: 0.9315, recall: 0.6671, relative_absolute_error: 0.7345, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.577, root_relative_squared_error: 1.212, scimark_benchmark: 940.3347, usercpu_time_millis: 140, usercpu_time_millis_testing: 70, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5373, kb_relative_information_score: -15609.5695, mean_absolute_error: 0.4694, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.5468, predictive_accuracy: 0.5306, prior_entropy: 0.9315, recall: 0.5306, relative_absolute_error: 1.0357, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.6851, root_relative_squared_error: 1.4392, scimark_benchmark: 916.5955, usercpu_time_millis: 6180, usercpu_time_millis_testing: 60, usercpu_time_millis_training: 6120,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6878, f_measure: 0.7234, kappa: 0.3838, kb_relative_information_score: 73156.1423, mean_absolute_error: 0.2733, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7216, predictive_accuracy: 0.7267, prior_entropy: 0.9315, recall: 0.7267, relative_absolute_error: 0.6029, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.5228, root_relative_squared_error: 1.0981, scimark_benchmark: 882.7843, usercpu_time_millis: 4895860, usercpu_time_millis_testing: 435550, usercpu_time_millis_training: 4460310,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6723, f_measure: 0.7019, kappa: 0.3435, kb_relative_information_score: 61726.755, mean_absolute_error: 0.2985, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7024, predictive_accuracy: 0.7015, prior_entropy: 0.9315, recall: 0.7015, relative_absolute_error: 0.6587, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.5464, root_relative_squared_error: 1.1477, scimark_benchmark: 939.449, usercpu_time_millis: 1279270, usercpu_time_millis_testing: 100, usercpu_time_millis_training: 1279170,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7597, f_measure: 0.7172, kappa: 0.3622, kb_relative_information_score: 40518.8102, mean_absolute_error: 0.3648, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7195, predictive_accuracy: 0.7294, prior_entropy: 0.9315, recall: 0.7294, relative_absolute_error: 0.8048, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.4276, root_relative_squared_error: 0.8982, scimark_benchmark: 938.202, usercpu_time_millis: 12240, usercpu_time_millis_testing: 70, usercpu_time_millis_training: 12170,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6685, f_measure: 0.7156, kappa: 0.359, kb_relative_information_score: 73376.8667, mean_absolute_error: 0.2728, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7172, predictive_accuracy: 0.7272, prior_entropy: 0.9315, recall: 0.7272, relative_absolute_error: 0.6019, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.5223, root_relative_squared_error: 1.0971, scimark_benchmark: 938.9967, usercpu_time_millis: 2120, usercpu_time_millis_testing: 70, usercpu_time_millis_training: 2050,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8308, f_measure: 0.7654, kappa: 0.4724, kb_relative_information_score: 62004.8976, mean_absolute_error: 0.3182, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7675, predictive_accuracy: 0.7729, prior_entropy: 0.9315, recall: 0.7729, relative_absolute_error: 0.7021, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.3947, root_relative_squared_error: 0.8291, scimark_benchmark: 1363.434, usercpu_time_millis: 110, usercpu_time_millis_testing: 100, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.836, f_measure: 0.7819, kappa: 0.5136, kb_relative_information_score: 89924.7045, mean_absolute_error: 0.2435, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7811, predictive_accuracy: 0.7849, prior_entropy: 0.9315, recall: 0.7849, relative_absolute_error: 0.5372, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.4075, root_relative_squared_error: 0.856, scimark_benchmark: 825.5282, usercpu_time_millis: 8230, usercpu_time_millis_testing: 230, usercpu_time_millis_training: 8000,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.832, f_measure: 0.7761, kappa: 0.5017, kb_relative_information_score: 78880.1363, mean_absolute_error: 0.2707, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7751, predictive_accuracy: 0.7785, prior_entropy: 0.9315, recall: 0.7785, relative_absolute_error: 0.5973, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.4005, root_relative_squared_error: 0.8413, scimark_benchmark: 1307.3269, usercpu_time_millis: 11410, usercpu_time_millis_testing: 3600, usercpu_time_millis_training: 7810,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7734, f_measure: 0.7571, kappa: 0.4686, kb_relative_information_score: 79629.7114, mean_absolute_error: 0.2635, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7597, predictive_accuracy: 0.7553, prior_entropy: 0.9315, recall: 0.7553, relative_absolute_error: 0.5814, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.4449, root_relative_squared_error: 0.9346, scimark_benchmark: 1301.9956, usercpu_time_millis: 90, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8158, f_measure: 0.7705, kappa: 0.4886, kb_relative_information_score: 70243.9565, mean_absolute_error: 0.2964, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7694, predictive_accuracy: 0.7733, prior_entropy: 0.9315, recall: 0.7733, relative_absolute_error: 0.6539, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.4032, root_relative_squared_error: 0.847, scimark_benchmark: 1066.7184, usercpu_time_millis: 270, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 250,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8221, f_measure: 0.7783, kappa: 0.5045, kb_relative_information_score: 72359.9015, mean_absolute_error: 0.294, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7777, predictive_accuracy: 0.7821, prior_entropy: 0.9315, recall: 0.7821, relative_absolute_error: 0.6487, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.3985, root_relative_squared_error: 0.8371, scimark_benchmark: 1327.6929, usercpu_time_millis: 24520, usercpu_time_millis_testing: 60, usercpu_time_millis_training: 24460,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5111, f_measure: 0.5428, kappa: 0.0211, kb_relative_information_score: -13864.4669, mean_absolute_error: 0.4656, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.5566, predictive_accuracy: 0.5344, prior_entropy: 0.9315, recall: 0.5344, relative_absolute_error: 1.0272, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.6823, root_relative_squared_error: 1.4333, scimark_benchmark: 1384.4418, usercpu_time_millis: 1270, usercpu_time_millis_testing: 150, usercpu_time_millis_training: 1120,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8381, f_measure: 0.7867, kappa: 0.5259, kb_relative_information_score: 81684.6004, mean_absolute_error: 0.2692, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7858, predictive_accuracy: 0.7886, prior_entropy: 0.9315, recall: 0.7886, relative_absolute_error: 0.594, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.3938, root_relative_squared_error: 0.8273, scimark_benchmark: 1466.6185, usercpu_time_millis: 4770, usercpu_time_millis_testing: 630, usercpu_time_millis_training: 4140,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6723, f_measure: 0.7019, kappa: 0.3435, kb_relative_information_score: 61726.755, mean_absolute_error: 0.2985, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7024, predictive_accuracy: 0.7015, prior_entropy: 0.9315, recall: 0.7015, relative_absolute_error: 0.6587, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.5464, root_relative_squared_error: 1.1477, scimark_benchmark: 1465.2979, usercpu_time_millis: 20, usercpu_time_millis_testing: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6491, f_measure: 0.7066, kappa: 0.3385, kb_relative_information_score: 77345.3081, mean_absolute_error: 0.264, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7377, predictive_accuracy: 0.736, prior_entropy: 0.9315, recall: 0.736, relative_absolute_error: 0.5825, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.5138, root_relative_squared_error: 1.0794, scimark_benchmark: 1028.5889, usercpu_time_millis: 13320, usercpu_time_millis_testing: 280, usercpu_time_millis_training: 13040,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5158, kb_relative_information_score: -2.0607, mean_absolute_error: 0.4532, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.4263, predictive_accuracy: 0.6529, prior_entropy: 0.9315, recall: 0.6529, relative_absolute_error: 1, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.476, root_relative_squared_error: 1, scimark_benchmark: 1054.3694, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8027, f_measure: 0.774, kappa: 0.4937, kb_relative_information_score: 68603.781, mean_absolute_error: 0.3038, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7741, predictive_accuracy: 0.779, prior_entropy: 0.9315, recall: 0.779, relative_absolute_error: 0.6703, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.4058, root_relative_squared_error: 0.8524, scimark_benchmark: 1066.833, usercpu_time_millis: 230, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 210,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8371, build_cpu_time: 542.7335, build_memory: 2948953723.2, f_measure: 0.7759, kappa: 0.5019, kb_relative_information_score: 80065.0596, mean_absolute_error: 0.2681, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7749, predictive_accuracy: 0.7777, prior_entropy: 0.9315, recall: 0.7777, relative_absolute_error: 0.5914, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.3975, root_relative_squared_error: 0.8351, scimark_benchmark: 940.8364,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8395, build_cpu_time: 1124.7544, build_memory: 992029732.8, f_measure: 0.7767, kappa: 0.5035, kb_relative_information_score: 80186.5927, mean_absolute_error: 0.2681, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7757, predictive_accuracy: 0.7787, prior_entropy: 0.9315, recall: 0.7787, relative_absolute_error: 0.5916, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.3957, root_relative_squared_error: 0.8313, scimark_benchmark: 946.197,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8409, build_cpu_time: 2386.827, build_memory: 1230122728.8, f_measure: 0.7772, kappa: 0.5046, kb_relative_information_score: 80263.6521, mean_absolute_error: 0.2681, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7762, predictive_accuracy: 0.7792, prior_entropy: 0.9315, recall: 0.7792, relative_absolute_error: 0.5915, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.3948, root_relative_squared_error: 0.8294, scimark_benchmark: 943.6957,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8416, build_cpu_time: 4502.8673, build_memory: 2333333753.6, f_measure: 0.7774, kappa: 0.505, kb_relative_information_score: 80349.1869, mean_absolute_error: 0.268, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7764, predictive_accuracy: 0.7794, prior_entropy: 0.9315, recall: 0.7794, relative_absolute_error: 0.5913, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.3944, root_relative_squared_error: 0.8284, scimark_benchmark: 947.2115,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8684, build_cpu_time: 37.4854, build_memory: 783741076, f_measure: 0.7907, kappa: 0.5314, kb_relative_information_score: 101800.9456, mean_absolute_error: 0.2119, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.791, predictive_accuracy: 0.795, prior_entropy: 0.9315, recall: 0.795, relative_absolute_error: 0.4674, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.4128, root_relative_squared_error: 0.8671, scimark_benchmark: 936.9135,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.857, build_cpu_time: 20.1103, build_memory: 1666071221.6, f_measure: 0.7746, kappa: 0.4939, kb_relative_information_score: 96130.4471, mean_absolute_error: 0.2239, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7761, predictive_accuracy: 0.781, prior_entropy: 0.9315, recall: 0.781, relative_absolute_error: 0.4939, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.4285, root_relative_squared_error: 0.9002, scimark_benchmark: 897.921,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8403, build_cpu_time: 9.9451, build_memory: 411547460.8, f_measure: 0.7537, kappa: 0.4468, kb_relative_information_score: 88245.0023, mean_absolute_error: 0.2406, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7542, predictive_accuracy: 0.7606, prior_entropy: 0.9315, recall: 0.7606, relative_absolute_error: 0.5308, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.4497, root_relative_squared_error: 0.9447, scimark_benchmark: 941.2105,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8144, build_cpu_time: 5.9618, build_memory: 468766771.2, f_measure: 0.7348, kappa: 0.4035, kb_relative_information_score: 80532.6449, mean_absolute_error: 0.2574, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7357, predictive_accuracy: 0.7437, prior_entropy: 0.9315, recall: 0.7437, relative_absolute_error: 0.5679, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.4751, root_relative_squared_error: 0.9979, scimark_benchmark: 944.0892,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7827, build_cpu_time: 3.1761, build_memory: 845043727.2, f_measure: 0.7259, kappa: 0.3836, kb_relative_information_score: 75758.569, mean_absolute_error: 0.2687, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7259, predictive_accuracy: 0.7346, prior_entropy: 0.9315, recall: 0.7346, relative_absolute_error: 0.5929, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.4902, root_relative_squared_error: 1.0298, scimark_benchmark: 931.9798,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8401, build_cpu_time: 1925.084, build_memory: 1610384397.6, f_measure: 0.7772, kappa: 0.4973, kb_relative_information_score: 63486.8252, mean_absolute_error: 0.3213, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.785, predictive_accuracy: 0.7873, prior_entropy: 0.9315, recall: 0.7873, relative_absolute_error: 0.7088, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.3908, root_relative_squared_error: 0.8209, scimark_benchmark: 944.3879,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8551, build_cpu_time: 17.2081, build_memory: 1094862480, f_measure: 0.7885, kappa: 0.5262, kb_relative_information_score: 74936.4138, mean_absolute_error: 0.2897, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.789, predictive_accuracy: 0.7931, prior_entropy: 0.9315, recall: 0.7931, relative_absolute_error: 0.6392, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.3799, root_relative_squared_error: 0.798, scimark_benchmark: 947.6184,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8545, build_cpu_time: 7.5438, build_memory: 767057432, f_measure: 0.7882, kappa: 0.5256, kb_relative_information_score: 74901.5711, mean_absolute_error: 0.2897, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7887, predictive_accuracy: 0.7928, prior_entropy: 0.9315, recall: 0.7928, relative_absolute_error: 0.6392, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.3802, root_relative_squared_error: 0.7987, scimark_benchmark: 941.5903,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8535, build_cpu_time: 3.9485, build_memory: 1770828607.2, f_measure: 0.7878, kappa: 0.5247, kb_relative_information_score: 74941.0251, mean_absolute_error: 0.2895, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.7882, predictive_accuracy: 0.7924, prior_entropy: 0.9315, recall: 0.7924, relative_absolute_error: 0.6388, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.3806, root_relative_squared_error: 0.7996, scimark_benchmark: 941.9282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8514, build_cpu_time: 1.981, build_memory: 1518770065.6, f_measure: 0.7868, kappa: 0.5227, kb_relative_information_score: 74904.5241, mean_absolute_error: 0.2893, mean_prior_absolute_error: 0.4532, number_of_instances: 196830, precision: 0.787, predictive_accuracy: 0.7912, prior_entropy: 0.9315, recall: 0.7912, relative_absolute_error: 0.6382, root_mean_prior_squared_error: 0.476, root_mean_squared_error: 0.3818, root_relative_squared_error: 0.802, scimark_benchmark: 945.3116,

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

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From your own software

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

OpenML APIs