OpenML
Supervised Classification on fri_c0_100_10

Supervised Classification on fri_c0_100_10

Task 3673 Supervised Classification fri_c0_100_10 754 runs submitted
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  • 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: 0.8903, f_measure: 0.8293, kappa: 0.6545, kb_relative_information_score: 65.2211, mean_absolute_error: 0.1725, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.8302, predictive_accuracy: 0.83, prior_entropy: 0.9931, recall: 0.83, relative_absolute_error: 0.3484, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.3869, root_relative_squared_error: 0.7777, scimark_benchmark: 935.6052, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8663, f_measure: 0.7795, kappa: 0.5538, kb_relative_information_score: 56.1608, mean_absolute_error: 0.2175, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.7796, predictive_accuracy: 0.78, prior_entropy: 0.9931, recall: 0.78, relative_absolute_error: 0.4393, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.4184, root_relative_squared_error: 0.8411, scimark_benchmark: 938.3115, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.839, f_measure: 0.7481, kappa: 0.4898, kb_relative_information_score: 46.753, mean_absolute_error: 0.2638, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.75, predictive_accuracy: 0.75, prior_entropy: 0.9931, recall: 0.75, relative_absolute_error: 0.5329, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.4483, root_relative_squared_error: 0.901, scimark_benchmark: 935.6052, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8016, f_measure: 0.7103, kappa: 0.4153, kb_relative_information_score: 41.1651, mean_absolute_error: 0.2919, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.7107, predictive_accuracy: 0.71, prior_entropy: 0.9931, recall: 0.71, relative_absolute_error: 0.5895, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.4626, root_relative_squared_error: 0.9299, scimark_benchmark: 935.6052,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3903, kb_relative_information_score: 8.7112, mean_absolute_error: 0.45, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.3025, predictive_accuracy: 0.55, prior_entropy: 0.9931, recall: 0.55, relative_absolute_error: 0.9089, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.6708, root_relative_squared_error: 1.3484, scimark_benchmark: 941.9549,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7291, f_measure: 0.7297, kappa: 0.4534, kb_relative_information_score: 42.7025, mean_absolute_error: 0.2859, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.7295, predictive_accuracy: 0.73, prior_entropy: 0.9931, recall: 0.73, relative_absolute_error: 0.5775, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.5036, root_relative_squared_error: 1.0123, scimark_benchmark: 942.6192,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7814, f_measure: 0.7142, kappa: 0.4227, kb_relative_information_score: 11.4073, mean_absolute_error: 0.451, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.7235, predictive_accuracy: 0.72, prior_entropy: 0.9931, recall: 0.72, relative_absolute_error: 0.911, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.4592, root_relative_squared_error: 0.9231, scimark_benchmark: 923.7471, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7869, f_measure: 0.7158, kappa: 0.4251, kb_relative_information_score: 18.1735, mean_absolute_error: 0.4203, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.7212, predictive_accuracy: 0.72, prior_entropy: 0.9931, recall: 0.72, relative_absolute_error: 0.8489, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.4427, root_relative_squared_error: 0.8898, scimark_benchmark: 933.0918, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4941, f_measure: 0.4951, kappa: -0.0225, kb_relative_information_score: -0.9777, mean_absolute_error: 0.4967, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.4937, predictive_accuracy: 0.5, prior_entropy: 0.9931, recall: 0.5, relative_absolute_error: 1.0032, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.5587, root_relative_squared_error: 1.123, scimark_benchmark: 899.1108,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.88, f_measure: 0.8, kappa: 0.596, kb_relative_information_score: 46.6629, mean_absolute_error: 0.2797, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.8, predictive_accuracy: 0.8, prior_entropy: 0.9931, recall: 0.8, relative_absolute_error: 0.5648, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.3719, root_relative_squared_error: 0.7476, scimark_benchmark: 930.0565, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8121, f_measure: 0.7302, kappa: 0.4556, kb_relative_information_score: 39.4704, mean_absolute_error: 0.3031, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.7306, predictive_accuracy: 0.73, prior_entropy: 0.9931, recall: 0.73, relative_absolute_error: 0.6121, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.4464, root_relative_squared_error: 0.8973, scimark_benchmark: 934.929, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8293, f_measure: 0.8302, kappa: 0.6573, kb_relative_information_score: 65.4957, mean_absolute_error: 0.17, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.8305, predictive_accuracy: 0.83, prior_entropy: 0.9931, recall: 0.83, relative_absolute_error: 0.3434, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.4123, root_relative_squared_error: 0.8288, scimark_benchmark: 928.8135, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8293, f_measure: 0.8302, kappa: 0.6573, kb_relative_information_score: 65.4957, mean_absolute_error: 0.17, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.8305, predictive_accuracy: 0.83, prior_entropy: 0.9931, recall: 0.83, relative_absolute_error: 0.3434, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.4123, root_relative_squared_error: 0.8288, scimark_benchmark: 946.8777,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4972, f_measure: 0.4971, kappa: -0.0183, kb_relative_information_score: -0.1827, mean_absolute_error: 0.4927, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.4959, predictive_accuracy: 0.5, prior_entropy: 0.9931, recall: 0.5, relative_absolute_error: 0.9951, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.543, root_relative_squared_error: 1.0914, scimark_benchmark: 945.0194,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4992, f_measure: 0.4971, kappa: -0.0183, kb_relative_information_score: -0.1037, mean_absolute_error: 0.4923, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.4959, predictive_accuracy: 0.5, prior_entropy: 0.9931, recall: 0.5, relative_absolute_error: 0.9943, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.5438, root_relative_squared_error: 1.0932, scimark_benchmark: 938.838,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4992, f_measure: 0.4971, kappa: -0.0183, kb_relative_information_score: -0.1037, mean_absolute_error: 0.4923, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.4959, predictive_accuracy: 0.5, prior_entropy: 0.9931, recall: 0.5, relative_absolute_error: 0.9943, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.5438, root_relative_squared_error: 1.0932, scimark_benchmark: 938.838, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4992, f_measure: 0.4971, kappa: -0.0183, kb_relative_information_score: -0.1037, mean_absolute_error: 0.4923, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.4959, predictive_accuracy: 0.5, prior_entropy: 0.9931, recall: 0.5, relative_absolute_error: 0.9943, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.5438, root_relative_squared_error: 1.0932, scimark_benchmark: 938.838, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4992, f_measure: 0.4971, kappa: -0.0183, kb_relative_information_score: -0.1037, mean_absolute_error: 0.4923, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.4959, predictive_accuracy: 0.5, prior_entropy: 0.9931, recall: 0.5, relative_absolute_error: 0.9943, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.5438, root_relative_squared_error: 1.0932, scimark_benchmark: 935.627, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8598, f_measure: 0.7778, kappa: 0.5501, kb_relative_information_score: 35.957, mean_absolute_error: 0.3351, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.7815, predictive_accuracy: 0.78, prior_entropy: 0.9931, recall: 0.78, relative_absolute_error: 0.6768, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.3933, root_relative_squared_error: 0.7905, scimark_benchmark: 922.5036,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9051, f_measure: 0.8092, kappa: 0.6138, kb_relative_information_score: 51.4931, mean_absolute_error: 0.2519, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.81, predictive_accuracy: 0.81, prior_entropy: 0.9931, recall: 0.81, relative_absolute_error: 0.5087, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.3594, root_relative_squared_error: 0.7225, scimark_benchmark: 946.9304, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4992, f_measure: 0.4971, kappa: -0.0183, kb_relative_information_score: -0.1037, mean_absolute_error: 0.4923, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.4959, predictive_accuracy: 0.5, prior_entropy: 0.9931, recall: 0.5, relative_absolute_error: 0.9943, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.5438, root_relative_squared_error: 1.0932, scimark_benchmark: 952.4682,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8024, f_measure: 0.7235, kappa: 0.4421, kb_relative_information_score: 38.8591, mean_absolute_error: 0.3104, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.7358, predictive_accuracy: 0.73, prior_entropy: 0.9931, recall: 0.73, relative_absolute_error: 0.627, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.4514, root_relative_squared_error: 0.9074, scimark_benchmark: 946.9304, usercpu_time_millis: 70, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8988, f_measure: 0.8279, kappa: 0.6516, kb_relative_information_score: 38.7562, mean_absolute_error: 0.3246, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.8343, predictive_accuracy: 0.83, prior_entropy: 0.9931, recall: 0.83, relative_absolute_error: 0.6556, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.3724, root_relative_squared_error: 0.7486, scimark_benchmark: 946.9304, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4941, f_measure: 0.4951, kappa: -0.0225, kb_relative_information_score: -0.9777, mean_absolute_error: 0.4967, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.4937, predictive_accuracy: 0.5, prior_entropy: 0.9931, recall: 0.5, relative_absolute_error: 1.0032, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.5587, root_relative_squared_error: 1.123, scimark_benchmark: 946.9304,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8293, f_measure: 0.8302, kappa: 0.6573, kb_relative_information_score: 65.4957, mean_absolute_error: 0.17, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.8305, predictive_accuracy: 0.83, prior_entropy: 0.9931, recall: 0.83, relative_absolute_error: 0.3434, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.4123, root_relative_squared_error: 0.8288, scimark_benchmark: 1286.2211,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4992, f_measure: 0.4971, kappa: -0.0183, kb_relative_information_score: -0.1037, mean_absolute_error: 0.4923, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.4959, predictive_accuracy: 0.5, prior_entropy: 0.9931, recall: 0.5, relative_absolute_error: 0.9943, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.5438, root_relative_squared_error: 1.0932, scimark_benchmark: 1346.2927,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4941, f_measure: 0.4951, kappa: -0.0225, kb_relative_information_score: -0.9777, mean_absolute_error: 0.4967, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.4937, predictive_accuracy: 0.5, prior_entropy: 0.9931, recall: 0.5, relative_absolute_error: 1.0032, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.5587, root_relative_squared_error: 1.123, scimark_benchmark: 1317.8359,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4992, f_measure: 0.4971, kappa: -0.0183, kb_relative_information_score: -0.1037, mean_absolute_error: 0.4923, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.4959, predictive_accuracy: 0.5, prior_entropy: 0.9931, recall: 0.5, relative_absolute_error: 0.9943, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.5438, root_relative_squared_error: 1.0932, scimark_benchmark: 1322.5413, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4992, f_measure: 0.4971, kappa: -0.0183, kb_relative_information_score: -0.1037, mean_absolute_error: 0.4923, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.4959, predictive_accuracy: 0.5, prior_entropy: 0.9931, recall: 0.5, relative_absolute_error: 0.9943, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.5438, root_relative_squared_error: 1.0932, scimark_benchmark: 926.6704,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8024, f_measure: 0.7235, kappa: 0.4421, kb_relative_information_score: 38.8591, mean_absolute_error: 0.3104, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.7358, predictive_accuracy: 0.73, prior_entropy: 0.9931, recall: 0.73, relative_absolute_error: 0.627, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.4514, root_relative_squared_error: 0.9074, scimark_benchmark: 1322.5413, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4992, f_measure: 0.4971, kappa: -0.0183, kb_relative_information_score: -0.1037, mean_absolute_error: 0.4923, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.4959, predictive_accuracy: 0.5, prior_entropy: 0.9931, recall: 0.5, relative_absolute_error: 0.9943, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.5438, root_relative_squared_error: 1.0932, scimark_benchmark: 1346.2927,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4941, f_measure: 0.4951, kappa: -0.0225, kb_relative_information_score: -0.9777, mean_absolute_error: 0.4967, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.4937, predictive_accuracy: 0.5, prior_entropy: 0.9931, recall: 0.5, relative_absolute_error: 1.0032, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.5587, root_relative_squared_error: 1.123, scimark_benchmark: 1340.9446,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4992, f_measure: 0.4971, kappa: -0.0183, kb_relative_information_score: -0.1037, mean_absolute_error: 0.4923, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.4959, predictive_accuracy: 0.5, prior_entropy: 0.9931, recall: 0.5, relative_absolute_error: 0.9943, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.5438, root_relative_squared_error: 1.0932, scimark_benchmark: 1313.8988,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4992, f_measure: 0.4971, kappa: -0.0183, kb_relative_information_score: -0.1037, mean_absolute_error: 0.4923, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.4959, predictive_accuracy: 0.5, prior_entropy: 0.9931, recall: 0.5, relative_absolute_error: 0.9943, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.5438, root_relative_squared_error: 1.0932, scimark_benchmark: 1313.8988,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8598, f_measure: 0.7778, kappa: 0.5501, kb_relative_information_score: 35.957, mean_absolute_error: 0.3351, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.7815, predictive_accuracy: 0.78, prior_entropy: 0.9931, recall: 0.78, relative_absolute_error: 0.6768, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.3933, root_relative_squared_error: 0.7905, scimark_benchmark: 1313.8988,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8121, f_measure: 0.7302, kappa: 0.4556, kb_relative_information_score: 39.4704, mean_absolute_error: 0.3031, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.7306, predictive_accuracy: 0.73, prior_entropy: 0.9931, recall: 0.73, relative_absolute_error: 0.6121, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.4464, root_relative_squared_error: 0.8973, scimark_benchmark: 1336.0954, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4992, f_measure: 0.4971, kappa: -0.0183, kb_relative_information_score: -0.1037, mean_absolute_error: 0.4923, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.4959, predictive_accuracy: 0.5, prior_entropy: 0.9931, recall: 0.5, relative_absolute_error: 0.9943, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.5438, root_relative_squared_error: 1.0932, scimark_benchmark: 908.2231,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4941, f_measure: 0.4951, kappa: -0.0225, kb_relative_information_score: -0.9777, mean_absolute_error: 0.4967, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.4937, predictive_accuracy: 0.5, prior_entropy: 0.9931, recall: 0.5, relative_absolute_error: 1.0032, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.5587, root_relative_squared_error: 1.123, scimark_benchmark: 933.1165,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4992, f_measure: 0.4971, kappa: -0.0183, kb_relative_information_score: -0.1037, mean_absolute_error: 0.4923, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.4959, predictive_accuracy: 0.5, prior_entropy: 0.9931, recall: 0.5, relative_absolute_error: 0.9943, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.5438, root_relative_squared_error: 1.0932, scimark_benchmark: 933.1165,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4992, f_measure: 0.4971, kappa: -0.0183, kb_relative_information_score: -0.1037, mean_absolute_error: 0.4923, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.4959, predictive_accuracy: 0.5, prior_entropy: 0.9931, recall: 0.5, relative_absolute_error: 0.9943, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.5438, root_relative_squared_error: 1.0932, scimark_benchmark: 933.1165,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4992, f_measure: 0.4971, kappa: -0.0183, kb_relative_information_score: -0.1037, mean_absolute_error: 0.4923, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.4959, predictive_accuracy: 0.5, prior_entropy: 0.9931, recall: 0.5, relative_absolute_error: 0.9943, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.5438, root_relative_squared_error: 1.0932, scimark_benchmark: 1342.6911,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8988, f_measure: 0.8279, kappa: 0.6516, kb_relative_information_score: 38.7562, mean_absolute_error: 0.3246, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.8343, predictive_accuracy: 0.83, prior_entropy: 0.9931, recall: 0.83, relative_absolute_error: 0.6556, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.3724, root_relative_squared_error: 0.7486, scimark_benchmark: 1312.0581, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.88, f_measure: 0.8, kappa: 0.596, kb_relative_information_score: 46.6629, mean_absolute_error: 0.2797, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.8, predictive_accuracy: 0.8, prior_entropy: 0.9931, recall: 0.8, relative_absolute_error: 0.5648, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.3719, root_relative_squared_error: 0.7476, scimark_benchmark: 1345.7204,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.88, f_measure: 0.8, kappa: 0.596, kb_relative_information_score: 46.6629, mean_absolute_error: 0.2797, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.8, predictive_accuracy: 0.8, prior_entropy: 0.9931, recall: 0.8, relative_absolute_error: 0.5648, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.3719, root_relative_squared_error: 0.7476, scimark_benchmark: 1328.941,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8121, f_measure: 0.7302, kappa: 0.4556, kb_relative_information_score: 39.4704, mean_absolute_error: 0.3031, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.7306, predictive_accuracy: 0.73, prior_entropy: 0.9931, recall: 0.73, relative_absolute_error: 0.6121, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.4464, root_relative_squared_error: 0.8973, scimark_benchmark: 916.6405, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4941, f_measure: 0.4951, kappa: -0.0225, kb_relative_information_score: -0.9777, mean_absolute_error: 0.4967, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.4937, predictive_accuracy: 0.5, prior_entropy: 0.9931, recall: 0.5, relative_absolute_error: 1.0032, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.5587, root_relative_squared_error: 1.123, scimark_benchmark: 1335.643,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4941, f_measure: 0.4951, kappa: -0.0225, kb_relative_information_score: -0.9777, mean_absolute_error: 0.4967, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.4937, predictive_accuracy: 0.5, prior_entropy: 0.9931, recall: 0.5, relative_absolute_error: 1.0032, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.5587, root_relative_squared_error: 1.123, scimark_benchmark: 922.1419,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7281, f_measure: 0.7279, kappa: 0.449, kb_relative_information_score: 40.3093, mean_absolute_error: 0.3013, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.7296, predictive_accuracy: 0.73, prior_entropy: 0.9931, recall: 0.73, relative_absolute_error: 0.6086, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.4791, root_relative_squared_error: 0.963, scimark_benchmark: 1059.8591,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6313, f_measure: 0.6309, kappa: 0.26, kb_relative_information_score: 24.9353, mean_absolute_error: 0.37, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.635, predictive_accuracy: 0.63, prior_entropy: 0.9931, recall: 0.63, relative_absolute_error: 0.7473, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.6083, root_relative_squared_error: 1.2227, scimark_benchmark: 950.6776,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9079, f_measure: 0.8699, kappa: 0.7368, kb_relative_information_score: 45.7279, mean_absolute_error: 0.2908, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.8699, predictive_accuracy: 0.87, prior_entropy: 0.9931, recall: 0.87, relative_absolute_error: 0.5874, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.3539, root_relative_squared_error: 0.7115, scimark_benchmark: 833.3193,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8121, f_measure: 0.7302, kappa: 0.4556, kb_relative_information_score: 39.4704, mean_absolute_error: 0.3031, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.7306, predictive_accuracy: 0.73, prior_entropy: 0.9931, recall: 0.73, relative_absolute_error: 0.6121, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.4464, root_relative_squared_error: 0.8973, scimark_benchmark: 1318.8785, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7446, f_measure: 0.74, kappa: 0.4747, kb_relative_information_score: 44.7305, mean_absolute_error: 0.2759, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.74, predictive_accuracy: 0.74, prior_entropy: 0.9931, recall: 0.74, relative_absolute_error: 0.5573, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.4936, root_relative_squared_error: 0.9921, scimark_benchmark: 1334.4761,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8121, f_measure: 0.7302, kappa: 0.4556, kb_relative_information_score: 39.4704, mean_absolute_error: 0.3031, mean_prior_absolute_error: 0.4951, number_of_instances: 100, precision: 0.7306, predictive_accuracy: 0.73, prior_entropy: 0.9931, recall: 0.73, relative_absolute_error: 0.6121, root_mean_prior_squared_error: 0.4975, root_mean_squared_error: 0.4464, root_relative_squared_error: 0.8973, scimark_benchmark: 1322.4968, usercpu_time_millis: 10, usercpu_time_millis_training: 10,

Metric:

Timeline

Plotting contribution timeline

Leaderboard

Rank Name Top Score Entries Highest rank

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

Challenge

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

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

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

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

Given inputs

Expected outputs

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

How to submit runs

Using your favorite machine learning environment

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

OpenML bootcamp

From your own software

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

OpenML APIs