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OpenML
Task
Supervised Classification on fri_c1_250_25

Supervised Classification on fri_c1_250_25

Task 3612 Supervised Classification fri_c1_250_25 558 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 study_7 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5639, f_measure: 0.5735, kappa: 0.1258, kb_relative_information_score: 17.8475, mean_absolute_error: 0.4548, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.5722, predictive_accuracy: 0.576, prior_entropy: 0.9852, recall: 0.576, relative_absolute_error: 0.9287, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.5481, root_relative_squared_error: 1.1078, scimark_benchmark: 854.5188, usercpu_time_millis: 50, usercpu_time_millis_testing: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5281, f_measure: 0.4827, kappa: 0.0631, kb_relative_information_score: 39.8015, mean_absolute_error: 0.408, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.6318, predictive_accuracy: 0.592, prior_entropy: 0.9852, recall: 0.592, relative_absolute_error: 0.8331, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.6387, root_relative_squared_error: 1.291, scimark_benchmark: 1304.9611, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4163, kb_relative_information_score: 29.5006, mean_absolute_error: 0.428, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.3272, predictive_accuracy: 0.572, prior_entropy: 0.9852, recall: 0.572, relative_absolute_error: 0.874, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.6542, root_relative_squared_error: 1.3222, scimark_benchmark: 1333.5799, usercpu_time_millis: 40, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.602, f_measure: 0.6131, kappa: 0.2064, kb_relative_information_score: 52.1625, mean_absolute_error: 0.384, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.6121, predictive_accuracy: 0.616, prior_entropy: 0.9852, recall: 0.616, relative_absolute_error: 0.7841, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.6197, root_relative_squared_error: 1.2524, scimark_benchmark: 1287.514, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.643, f_measure: 0.5808, kappa: 0.1403, kb_relative_information_score: 25.9449, mean_absolute_error: 0.4417, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.5795, predictive_accuracy: 0.584, prior_entropy: 0.9852, recall: 0.584, relative_absolute_error: 0.9019, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.4878, root_relative_squared_error: 0.986, scimark_benchmark: 938.343, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5728, f_measure: 0.5845, kappa: 0.1475, kb_relative_information_score: 37.7413, mean_absolute_error: 0.412, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.5832, predictive_accuracy: 0.588, prior_entropy: 0.9852, recall: 0.588, relative_absolute_error: 0.8413, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.6419, root_relative_squared_error: 1.2973, scimark_benchmark: 1331.6907, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6321, f_measure: 0.5881, kappa: 0.1548, kb_relative_information_score: 31.6943, mean_absolute_error: 0.4291, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.5869, predictive_accuracy: 0.592, prior_entropy: 0.9852, recall: 0.592, relative_absolute_error: 0.8763, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.509, root_relative_squared_error: 1.0287, scimark_benchmark: 916.9356, usercpu_time_millis: 480, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 430,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8826, f_measure: 0.8277, kappa: 0.6475, kb_relative_information_score: 134.6709, mean_absolute_error: 0.2344, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.8276, predictive_accuracy: 0.828, prior_entropy: 0.9852, recall: 0.828, relative_absolute_error: 0.4787, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.3667, root_relative_squared_error: 0.7411, scimark_benchmark: 1337.7959, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8883, f_measure: 0.8277, kappa: 0.6475, kb_relative_information_score: 140.7134, mean_absolute_error: 0.2239, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.8276, predictive_accuracy: 0.828, prior_entropy: 0.9852, recall: 0.828, relative_absolute_error: 0.4571, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.3593, root_relative_squared_error: 0.7263, scimark_benchmark: 1368.9272, usercpu_time_millis: 30, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9052, f_measure: 0.8478, kappa: 0.6888, kb_relative_information_score: 157.0707, mean_absolute_error: 0.1898, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.8477, predictive_accuracy: 0.848, prior_entropy: 0.9852, recall: 0.848, relative_absolute_error: 0.3876, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.3413, root_relative_squared_error: 0.6899, scimark_benchmark: 1372.2145, usercpu_time_millis: 170, usercpu_time_millis_training: 170,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9439, f_measure: 0.8549, kappa: 0.7024, kb_relative_information_score: 100.799, mean_absolute_error: 0.3197, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.8567, predictive_accuracy: 0.856, prior_entropy: 0.9852, recall: 0.856, relative_absolute_error: 0.6529, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.352, root_relative_squared_error: 0.7113, scimark_benchmark: 1318.1432, usercpu_time_millis: 100, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7094, f_measure: 0.7184, kappa: 0.4227, kb_relative_information_score: 105.7272, mean_absolute_error: 0.28, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.7182, predictive_accuracy: 0.72, prior_entropy: 0.9852, recall: 0.72, relative_absolute_error: 0.5718, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.5292, root_relative_squared_error: 1.0694, scimark_benchmark: 1280.6952,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9098, f_measure: 0.88, kappa: 0.7549, kb_relative_information_score: 166.5155, mean_absolute_error: 0.1761, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.88, predictive_accuracy: 0.88, prior_entropy: 0.9852, recall: 0.88, relative_absolute_error: 0.3597, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.3209, root_relative_squared_error: 0.6486, scimark_benchmark: 1318.5526,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8474, f_measure: 0.8517, kappa: 0.6967, kb_relative_information_score: 157.8082, mean_absolute_error: 0.1898, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.8517, predictive_accuracy: 0.852, prior_entropy: 0.9852, recall: 0.852, relative_absolute_error: 0.3876, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.3659, root_relative_squared_error: 0.7394, scimark_benchmark: 1355.7054, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5916, f_measure: 0.5901, kappa: 0.1788, kb_relative_information_score: 37.7413, mean_absolute_error: 0.412, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.6005, predictive_accuracy: 0.588, prior_entropy: 0.9852, recall: 0.588, relative_absolute_error: 0.8413, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.6419, root_relative_squared_error: 1.2973, scimark_benchmark: 1320.2556, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.2566, kb_relative_information_score: -44.6659, mean_absolute_error: 0.572, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.1832, predictive_accuracy: 0.428, prior_entropy: 0.9852, recall: 0.428, relative_absolute_error: 1.168, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.7563, root_relative_squared_error: 1.5285, scimark_benchmark: 1280.6952, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8663, f_measure: 0.8636, kappa: 0.7209, kb_relative_information_score: 174.2533, mean_absolute_error: 0.1501, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.8637, predictive_accuracy: 0.864, prior_entropy: 0.9852, recall: 0.864, relative_absolute_error: 0.3064, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.36, root_relative_squared_error: 0.7277, scimark_benchmark: 1465.2979, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7514, f_measure: 0.7561, kappa: 0.5023, kb_relative_information_score: 124.2688, mean_absolute_error: 0.244, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.7563, predictive_accuracy: 0.756, prior_entropy: 0.9852, recall: 0.756, relative_absolute_error: 0.4983, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.494, root_relative_squared_error: 0.9983, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8249, f_measure: 0.8281, kappa: 0.6491, kb_relative_information_score: 161.3521, mean_absolute_error: 0.172, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.8282, predictive_accuracy: 0.828, prior_entropy: 0.9852, recall: 0.828, relative_absolute_error: 0.3512, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.4147, root_relative_squared_error: 0.8382, scimark_benchmark: 1353.5686, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4828, f_measure: 0.4163, kb_relative_information_score: -0.093, mean_absolute_error: 0.4898, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.3272, predictive_accuracy: 0.572, prior_entropy: 0.9852, recall: 0.572, relative_absolute_error: 1.0002, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.4949, root_relative_squared_error: 1.0002, scimark_benchmark: 1503.3362,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8644, f_measure: 0.8593, kappa: 0.7117, kb_relative_information_score: 174.0454, mean_absolute_error: 0.1505, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.86, predictive_accuracy: 0.86, prior_entropy: 0.9852, recall: 0.86, relative_absolute_error: 0.3073, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.3581, root_relative_squared_error: 0.7238, scimark_benchmark: 1465.2979, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6925, f_measure: 0.6336, kappa: 0.2486, kb_relative_information_score: 61.8507, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.6328, predictive_accuracy: 0.636, prior_entropy: 0.9852, recall: 0.636, relative_absolute_error: 0.7472, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.5772, root_relative_squared_error: 1.1666, scimark_benchmark: 931.2336, usercpu_time_millis: 120, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6402, f_measure: 0.6211, kappa: 0.2229, kb_relative_information_score: 45.045, mean_absolute_error: 0.4037, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.6203, predictive_accuracy: 0.624, prior_entropy: 0.9852, recall: 0.624, relative_absolute_error: 0.8243, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.5377, root_relative_squared_error: 1.0867, scimark_benchmark: 945.6434, usercpu_time_millis: 50, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6406, f_measure: 0.6175, kappa: 0.2156, kb_relative_information_score: 43.0416, mean_absolute_error: 0.4081, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.6165, predictive_accuracy: 0.62, prior_entropy: 0.9852, recall: 0.62, relative_absolute_error: 0.8334, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.5246, root_relative_squared_error: 1.0603, scimark_benchmark: 941.7954, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6475, f_measure: 0.6218, kappa: 0.2248, kb_relative_information_score: 43.8839, mean_absolute_error: 0.4075, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.6209, predictive_accuracy: 0.624, prior_entropy: 0.9852, recall: 0.624, relative_absolute_error: 0.8321, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.5139, root_relative_squared_error: 1.0387, scimark_benchmark: 923.7642, usercpu_time_millis: 50, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6475, f_measure: 0.6218, kappa: 0.2248, kb_relative_information_score: 43.8839, mean_absolute_error: 0.4075, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.6209, predictive_accuracy: 0.624, prior_entropy: 0.9852, recall: 0.624, relative_absolute_error: 0.8321, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.5139, root_relative_squared_error: 1.0387, scimark_benchmark: 894.7455, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9357, f_measure: 0.8556, kappa: 0.7045, kb_relative_information_score: 175.7773, mean_absolute_error: 0.1443, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.8557, predictive_accuracy: 0.856, prior_entropy: 0.9852, recall: 0.856, relative_absolute_error: 0.2946, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.3486, root_relative_squared_error: 0.7045, scimark_benchmark: 894.7455, usercpu_time_millis: 390, usercpu_time_millis_training: 390,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9272, f_measure: 0.8441, kappa: 0.6818, kb_relative_information_score: 171.7618, mean_absolute_error: 0.1526, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.8442, predictive_accuracy: 0.844, prior_entropy: 0.9852, recall: 0.844, relative_absolute_error: 0.3116, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.3491, root_relative_squared_error: 0.7055, scimark_benchmark: 943.2817, usercpu_time_millis: 190, usercpu_time_millis_training: 190,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8951, f_measure: 0.8119, kappa: 0.6156, kb_relative_information_score: 150.5235, mean_absolute_error: 0.1942, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.8118, predictive_accuracy: 0.812, prior_entropy: 0.9852, recall: 0.812, relative_absolute_error: 0.3967, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.3822, root_relative_squared_error: 0.7725, scimark_benchmark: 942.1229, usercpu_time_millis: 100, usercpu_time_millis_training: 100,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8185, f_measure: 0.7644, kappa: 0.5197, kb_relative_information_score: 110.4495, mean_absolute_error: 0.2759, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.765, predictive_accuracy: 0.764, prior_entropy: 0.9852, recall: 0.764, relative_absolute_error: 0.5634, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.4453, root_relative_squared_error: 0.9, scimark_benchmark: 922.9039, usercpu_time_millis: 70, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.758, f_measure: 0.7126, kappa: 0.4146, kb_relative_information_score: 91.7756, mean_absolute_error: 0.3106, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.7136, predictive_accuracy: 0.712, prior_entropy: 0.9852, recall: 0.712, relative_absolute_error: 0.6342, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.4818, root_relative_squared_error: 0.9738, scimark_benchmark: 938.9865, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9327, f_measure: 0.8439, kappa: 0.681, kb_relative_information_score: 165.6991, mean_absolute_error: 0.1649, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.8438, predictive_accuracy: 0.844, prior_entropy: 0.9852, recall: 0.844, relative_absolute_error: 0.3368, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.3485, root_relative_squared_error: 0.7044, scimark_benchmark: 936.6206, usercpu_time_millis: 190, usercpu_time_millis_training: 190,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9333, f_measure: 0.8474, kappa: 0.6874, kb_relative_information_score: 157.1353, mean_absolute_error: 0.1904, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.8477, predictive_accuracy: 0.848, prior_entropy: 0.9852, recall: 0.848, relative_absolute_error: 0.3888, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.3199, root_relative_squared_error: 0.6465, scimark_benchmark: 924.6116, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6475, build_cpu_time: 0.0422, build_memory: 1617965369.6, f_measure: 0.6218, kappa: 0.2248, kb_relative_information_score: 43.8839, mean_absolute_error: 0.4075, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.6209, predictive_accuracy: 0.624, prior_entropy: 0.9852, recall: 0.624, relative_absolute_error: 0.8321, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.5139, root_relative_squared_error: 1.0387, scimark_benchmark: 943.2074,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9165, build_cpu_time: 8.7025, build_memory: 505887602.4, f_measure: 0.8483, kappa: 0.691, kb_relative_information_score: 163.1029, mean_absolute_error: 0.173, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.8491, predictive_accuracy: 0.848, prior_entropy: 0.9852, recall: 0.848, relative_absolute_error: 0.3533, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.3503, root_relative_squared_error: 0.708, scimark_benchmark: 872.1114,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9309, build_cpu_time: 19.256, build_memory: 394126398.4, f_measure: 0.8721, kappa: 0.7392, kb_relative_information_score: 181.4094, mean_absolute_error: 0.1346, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.8724, predictive_accuracy: 0.872, prior_entropy: 0.9852, recall: 0.872, relative_absolute_error: 0.2749, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.3242, root_relative_squared_error: 0.6553, scimark_benchmark: 889.6909,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8856, build_cpu_time: 16.1722, build_memory: 1195875575.2, f_measure: 0.8513, kappa: 0.6952, kb_relative_information_score: 173.2358, mean_absolute_error: 0.1491, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.8519, predictive_accuracy: 0.852, prior_entropy: 0.9852, recall: 0.852, relative_absolute_error: 0.3046, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.383, root_relative_squared_error: 0.7741, scimark_benchmark: 945.0532,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8849, build_cpu_time: 8.4331, build_memory: 1455820285.6, f_measure: 0.8199, kappa: 0.6319, kb_relative_information_score: 158.3274, mean_absolute_error: 0.1774, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.8198, predictive_accuracy: 0.82, prior_entropy: 0.9852, recall: 0.82, relative_absolute_error: 0.3623, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.4129, root_relative_squared_error: 0.8345, scimark_benchmark: 945.0554,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.86, build_cpu_time: 3.9309, build_memory: 853570512, f_measure: 0.803, kappa: 0.5964, kb_relative_information_score: 149.1694, mean_absolute_error: 0.1955, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.8033, predictive_accuracy: 0.804, prior_entropy: 0.9852, recall: 0.804, relative_absolute_error: 0.3992, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.4266, root_relative_squared_error: 0.8622, scimark_benchmark: 907.4175,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9335, build_cpu_time: 0.9361, build_memory: 775451754.4, f_measure: 0.8713, kappa: 0.7361, kb_relative_information_score: 182.8679, mean_absolute_error: 0.1302, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.8724, predictive_accuracy: 0.872, prior_entropy: 0.9852, recall: 0.872, relative_absolute_error: 0.2659, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.3484, root_relative_squared_error: 0.7041, scimark_benchmark: 874.7324,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9316, build_cpu_time: 2.0414, build_memory: 655071223.2, f_measure: 0.8871, kappa: 0.7685, kb_relative_information_score: 193.1531, mean_absolute_error: 0.1102, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.8893, predictive_accuracy: 0.888, prior_entropy: 0.9852, recall: 0.888, relative_absolute_error: 0.2251, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.3188, root_relative_squared_error: 0.6443, scimark_benchmark: 942.5053,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8997, build_cpu_time: 8.3253, build_memory: 575568888, f_measure: 0.8838, kappa: 0.7622, kb_relative_information_score: 190.0137, mean_absolute_error: 0.1165, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.8838, predictive_accuracy: 0.884, prior_entropy: 0.9852, recall: 0.884, relative_absolute_error: 0.2378, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.3406, root_relative_squared_error: 0.6883, scimark_benchmark: 913.3372,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8996, build_cpu_time: 1.2001, build_memory: 932304772.8, f_measure: 0.863, kappa: 0.7189, kb_relative_information_score: 178.3435, mean_absolute_error: 0.1394, mean_prior_absolute_error: 0.4897, number_of_instances: 250, precision: 0.8648, predictive_accuracy: 0.864, prior_entropy: 0.9852, recall: 0.864, relative_absolute_error: 0.2846, root_mean_prior_squared_error: 0.4948, root_mean_squared_error: 0.3675, root_relative_squared_error: 0.7428, scimark_benchmark: 902.712,

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

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