OpenML
Supervised Classification on colic

Supervised Classification on colic

Task 27 Supervised Classification colic 754 runs submitted
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  • basic mythbusting mythbusting_1 study_1 study_107 study_15 study_20 study_41 study_73 under100k
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8373, f_measure: 0.7951, kappa: 0.5549, kb_relative_information_score: 195.2089, mean_absolute_error: 0.2166, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.7964, predictive_accuracy: 0.7989, prior_entropy: 0.9509, recall: 0.7989, relative_absolute_error: 0.4646, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4104, root_relative_squared_error: 0.8501, scimark_benchmark: 939.6009,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8894, f_measure: 0.8598, kappa: 0.6966, kb_relative_information_score: 208.9476, mean_absolute_error: 0.2092, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8606, predictive_accuracy: 0.8614, prior_entropy: 0.9509, recall: 0.8614, relative_absolute_error: 0.4487, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3425, root_relative_squared_error: 0.7096, scimark_benchmark: 944.9607,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8492, f_measure: 0.8375, kappa: 0.6479, kb_relative_information_score: 236.971, mean_absolute_error: 0.1611, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8384, predictive_accuracy: 0.8397, prior_entropy: 0.9509, recall: 0.8397, relative_absolute_error: 0.3455, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3959, root_relative_squared_error: 0.8202, scimark_benchmark: 942.3854,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8889, f_measure: 0.8323, kappa: 0.6371, kb_relative_information_score: 165.7626, mean_absolute_error: 0.2713, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8327, predictive_accuracy: 0.8342, prior_entropy: 0.9509, recall: 0.8342, relative_absolute_error: 0.5821, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3506, root_relative_squared_error: 0.7264, scimark_benchmark: 949.3332,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8904, f_measure: 0.854, kappa: 0.6837, kb_relative_information_score: 194.6403, mean_absolute_error: 0.2341, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8552, predictive_accuracy: 0.856, prior_entropy: 0.9509, recall: 0.856, relative_absolute_error: 0.5023, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3406, root_relative_squared_error: 0.7057, scimark_benchmark: 949.0891,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7572, f_measure: 0.7743, kappa: 0.5152, kb_relative_information_score: 184.4394, mean_absolute_error: 0.2255, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.7741, predictive_accuracy: 0.7745, prior_entropy: 0.9509, recall: 0.7745, relative_absolute_error: 0.4838, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4749, root_relative_squared_error: 0.9839, scimark_benchmark: 911.5572,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.553, f_measure: 0.5717, kappa: 0.1297, kb_relative_information_score: 98.2863, mean_absolute_error: 0.3315, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.7602, predictive_accuracy: 0.6685, prior_entropy: 0.9509, recall: 0.6685, relative_absolute_error: 0.7112, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.5758, root_relative_squared_error: 1.1929, scimark_benchmark: 947.9981,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8544, f_measure: 0.8241, kappa: 0.6169, kb_relative_information_score: 178.3899, mean_absolute_error: 0.2489, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8294, predictive_accuracy: 0.8288, prior_entropy: 0.9509, recall: 0.8288, relative_absolute_error: 0.534, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3661, root_relative_squared_error: 0.7585, scimark_benchmark: 922.4456,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8504, f_measure: 0.8316, kappa: 0.6348, kb_relative_information_score: 186.0312, mean_absolute_error: 0.2424, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8329, predictive_accuracy: 0.8342, prior_entropy: 0.9509, recall: 0.8342, relative_absolute_error: 0.5199, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3624, root_relative_squared_error: 0.7507, scimark_benchmark: 948.113,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8454, f_measure: 0.8034, kappa: 0.5763, kb_relative_information_score: 170.0826, mean_absolute_error: 0.257, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8029, predictive_accuracy: 0.8043, prior_entropy: 0.9509, recall: 0.8043, relative_absolute_error: 0.5512, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3827, root_relative_squared_error: 0.7928, scimark_benchmark: 947.5778,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8021, f_measure: 0.8066, kappa: 0.5803, kb_relative_information_score: 159.9067, mean_absolute_error: 0.278, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8076, predictive_accuracy: 0.8098, prior_entropy: 0.9509, recall: 0.8098, relative_absolute_error: 0.5965, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3794, root_relative_squared_error: 0.7859, scimark_benchmark: 947.4568,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8869, f_measure: 0.8537, kappa: 0.6827, kb_relative_information_score: 195.8618, mean_absolute_error: 0.2323, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8555, predictive_accuracy: 0.856, prior_entropy: 0.9509, recall: 0.856, relative_absolute_error: 0.4983, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.342, root_relative_squared_error: 0.7085, scimark_benchmark: 948.904,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8292, f_measure: 0.8045, kappa: 0.5763, kb_relative_information_score: 194.4541, mean_absolute_error: 0.2173, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8047, predictive_accuracy: 0.8071, prior_entropy: 0.9509, recall: 0.8071, relative_absolute_error: 0.4661, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3922, root_relative_squared_error: 0.8125, scimark_benchmark: 948.6302,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5487, f_measure: 0.5681, kappa: 0.1187, kb_relative_information_score: 93.8681, mean_absolute_error: 0.337, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.7205, predictive_accuracy: 0.663, prior_entropy: 0.9509, recall: 0.663, relative_absolute_error: 0.7228, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.5805, root_relative_squared_error: 1.2026, scimark_benchmark: 945.3969,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.862, f_measure: 0.8171, kappa: 0.6129, kb_relative_information_score: 163.1264, mean_absolute_error: 0.2745, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.822, predictive_accuracy: 0.8152, prior_entropy: 0.9509, recall: 0.8152, relative_absolute_error: 0.5889, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3711, root_relative_squared_error: 0.7688, scimark_benchmark: 947.3514,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7639, f_measure: 0.7778, kappa: 0.5247, kb_relative_information_score: 186.6485, mean_absolute_error: 0.2228, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.7787, predictive_accuracy: 0.7772, prior_entropy: 0.9509, recall: 0.7772, relative_absolute_error: 0.478, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.472, root_relative_squared_error: 0.978, scimark_benchmark: 916.6602,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8139, f_measure: 0.8171, kappa: 0.6129, kb_relative_information_score: 217.5752, mean_absolute_error: 0.1848, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.822, predictive_accuracy: 0.8152, prior_entropy: 0.9509, recall: 0.8152, relative_absolute_error: 0.3964, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4299, root_relative_squared_error: 0.8906, scimark_benchmark: 913.323,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5435, f_measure: 0.5594, kappa: 0.1066, kb_relative_information_score: 91.6591, mean_absolute_error: 0.3397, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.7311, predictive_accuracy: 0.6603, prior_entropy: 0.9509, recall: 0.6603, relative_absolute_error: 0.7287, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.5828, root_relative_squared_error: 1.2074, scimark_benchmark: 941.8859,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8054, f_measure: 0.8181, kappa: 0.6099, kb_relative_information_score: 219.7843, mean_absolute_error: 0.1821, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8182, predictive_accuracy: 0.8179, prior_entropy: 0.9509, recall: 0.8179, relative_absolute_error: 0.3906, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4267, root_relative_squared_error: 0.884, scimark_benchmark: 947.248,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8142, f_measure: 0.8404, kappa: 0.6544, kb_relative_information_score: 179.2725, mean_absolute_error: 0.2545, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8411, predictive_accuracy: 0.8424, prior_entropy: 0.9509, recall: 0.8424, relative_absolute_error: 0.546, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3624, root_relative_squared_error: 0.7508, scimark_benchmark: 911.0981,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5147, f_measure: 0.5119, kappa: 0.0368, kb_relative_information_score: 76.1957, mean_absolute_error: 0.3587, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.7714, predictive_accuracy: 0.6413, prior_entropy: 0.9509, recall: 0.6413, relative_absolute_error: 0.7695, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.5989, root_relative_squared_error: 1.2408,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4878, f_measure: 0.4875, kb_relative_information_score: -0.1525, mean_absolute_error: 0.4662, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.3974, predictive_accuracy: 0.6304, prior_entropy: 0.9509, recall: 0.6304, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4827, root_relative_squared_error: 1.0001, scimark_benchmark: 948.3842,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8956, f_measure: 0.8476, kappa: 0.6724, kb_relative_information_score: 210.5131, mean_absolute_error: 0.2079, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8474, predictive_accuracy: 0.8478, prior_entropy: 0.9509, recall: 0.8478, relative_absolute_error: 0.446, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3378, root_relative_squared_error: 0.6998, scimark_benchmark: 946.2219,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5368, f_measure: 0.5464, kappa: 0.091, kb_relative_information_score: 89.45, mean_absolute_error: 0.3424, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.7781, predictive_accuracy: 0.6576, prior_entropy: 0.9509, recall: 0.6576, relative_absolute_error: 0.7345, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.5851, root_relative_squared_error: 1.2123, scimark_benchmark: 948.1068,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8115, f_measure: 0.799, kappa: 0.5613, kb_relative_information_score: 189.5719, mean_absolute_error: 0.2187, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.81, predictive_accuracy: 0.8071, prior_entropy: 0.9509, recall: 0.8071, relative_absolute_error: 0.4691, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.415, root_relative_squared_error: 0.8598, scimark_benchmark: 941.4753,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5331, f_measure: 0.5408, kappa: 0.082, kb_relative_information_score: 87.241, mean_absolute_error: 0.3451, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.777, predictive_accuracy: 0.6549, prior_entropy: 0.9509, recall: 0.6549, relative_absolute_error: 0.7403, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.5875, root_relative_squared_error: 1.2171,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8123, f_measure: 0.855, kappa: 0.6843, kb_relative_information_score: 189.9308, mean_absolute_error: 0.2424, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.861, predictive_accuracy: 0.8587, prior_entropy: 0.9509, recall: 0.8587, relative_absolute_error: 0.52, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3508, root_relative_squared_error: 0.7267, scimark_benchmark: 939.3388,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8492, f_measure: 0.8275, kappa: 0.6275, kb_relative_information_score: 194.2376, mean_absolute_error: 0.2257, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8273, predictive_accuracy: 0.8288, prior_entropy: 0.9509, recall: 0.8288, relative_absolute_error: 0.4842, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3778, root_relative_squared_error: 0.7827, scimark_benchmark: 947.052,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8476, f_measure: 0.8124, kappa: 0.597, kb_relative_information_score: 181.3299, mean_absolute_error: 0.2414, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8122, predictive_accuracy: 0.8125, prior_entropy: 0.9509, recall: 0.8125, relative_absolute_error: 0.5178, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3795, root_relative_squared_error: 0.7861, scimark_benchmark: 949.068,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8492, f_measure: 0.8275, kappa: 0.6275, kb_relative_information_score: 194.2376, mean_absolute_error: 0.2257, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8273, predictive_accuracy: 0.8288, prior_entropy: 0.9509, recall: 0.8288, relative_absolute_error: 0.4842, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3778, root_relative_squared_error: 0.7827, scimark_benchmark: 944.763,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.815, f_measure: 0.8372, kappa: 0.6468, kb_relative_information_score: 237.4567, mean_absolute_error: 0.1603, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8386, predictive_accuracy: 0.8397, prior_entropy: 0.9509, recall: 0.8397, relative_absolute_error: 0.3439, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4004, root_relative_squared_error: 0.8295, scimark_benchmark: 951.0852,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8123, f_measure: 0.855, kappa: 0.6843, kb_relative_information_score: 189.9308, mean_absolute_error: 0.2424, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.861, predictive_accuracy: 0.8587, prior_entropy: 0.9509, recall: 0.8587, relative_absolute_error: 0.52, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3508, root_relative_squared_error: 0.7267, scimark_benchmark: 947.2215,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8212, f_measure: 0.8494, kappa: 0.6721, kb_relative_information_score: 189.72, mean_absolute_error: 0.2415, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8552, predictive_accuracy: 0.8533, prior_entropy: 0.9509, recall: 0.8533, relative_absolute_error: 0.5181, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3533, root_relative_squared_error: 0.732, scimark_benchmark: 944.7398,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8514, f_measure: 0.8175, kappa: 0.6075, kb_relative_information_score: 167.7407, mean_absolute_error: 0.2639, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8172, predictive_accuracy: 0.8179, prior_entropy: 0.9509, recall: 0.8179, relative_absolute_error: 0.5661, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3729, root_relative_squared_error: 0.7725, scimark_benchmark: 943.6946,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5404, f_measure: 0.552, kappa: 0.0999, kb_relative_information_score: 91.6591, mean_absolute_error: 0.3397, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.7793, predictive_accuracy: 0.6603, prior_entropy: 0.9509, recall: 0.6603, relative_absolute_error: 0.7287, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.5828, root_relative_squared_error: 1.2074, scimark_benchmark: 949.5642,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8006, f_measure: 0.7688, kappa: 0.5118, kb_relative_information_score: 168.6939, mean_absolute_error: 0.2471, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.775, predictive_accuracy: 0.7663, prior_entropy: 0.9509, recall: 0.7663, relative_absolute_error: 0.5301, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.465, root_relative_squared_error: 0.9633, scimark_benchmark: 948.0903,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8948, f_measure: 0.8462, kappa: 0.6674, kb_relative_information_score: 167.3908, mean_absolute_error: 0.2709, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8466, predictive_accuracy: 0.8478, prior_entropy: 0.9509, recall: 0.8478, relative_absolute_error: 0.5811, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3459, root_relative_squared_error: 0.7166, scimark_benchmark: 916.4,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8139, f_measure: 0.8171, kappa: 0.6129, kb_relative_information_score: 217.5752, mean_absolute_error: 0.1848, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.822, predictive_accuracy: 0.8152, prior_entropy: 0.9509, recall: 0.8152, relative_absolute_error: 0.3964, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4299, root_relative_squared_error: 0.8906, scimark_benchmark: 909.0515,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5435, f_measure: 0.5594, kappa: 0.1066, kb_relative_information_score: 91.6591, mean_absolute_error: 0.3397, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.7311, predictive_accuracy: 0.6603, prior_entropy: 0.9509, recall: 0.6603, relative_absolute_error: 0.7287, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.5828, root_relative_squared_error: 1.2074, scimark_benchmark: 949.9087,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8335, f_measure: 0.8117, kappa: 0.5945, kb_relative_information_score: 197.2632, mean_absolute_error: 0.2173, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8113, predictive_accuracy: 0.8125, prior_entropy: 0.9509, recall: 0.8125, relative_absolute_error: 0.4661, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3951, root_relative_squared_error: 0.8185, scimark_benchmark: 946.8699,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7885, f_measure: 0.804, kappa: 0.5788, kb_relative_information_score: 208.739, mean_absolute_error: 0.1957, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8038, predictive_accuracy: 0.8043, prior_entropy: 0.9509, recall: 0.8043, relative_absolute_error: 0.4197, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4423, root_relative_squared_error: 0.9164, scimark_benchmark: 936.2183,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5478, f_measure: 0.5628, kappa: 0.1176, kb_relative_information_score: 96.0772, mean_absolute_error: 0.3342, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.7816, predictive_accuracy: 0.6658, prior_entropy: 0.9509, recall: 0.6658, relative_absolute_error: 0.717, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.5781, root_relative_squared_error: 1.1977, scimark_benchmark: 948.1145,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7572, f_measure: 0.7743, kappa: 0.5152, kb_relative_information_score: 184.4394, mean_absolute_error: 0.2255, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.7741, predictive_accuracy: 0.7745, prior_entropy: 0.9509, recall: 0.7745, relative_absolute_error: 0.4838, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4749, root_relative_squared_error: 0.9839, scimark_benchmark: 947.7151,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.804, f_measure: 0.8498, kappa: 0.6732, kb_relative_information_score: 189.8693, mean_absolute_error: 0.2424, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8545, predictive_accuracy: 0.8533, prior_entropy: 0.9509, recall: 0.8533, relative_absolute_error: 0.5201, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.357, root_relative_squared_error: 0.7397, scimark_benchmark: 949.0607,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8893, f_measure: 0.8456, kappa: 0.6653, kb_relative_information_score: 194.0179, mean_absolute_error: 0.2347, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8469, predictive_accuracy: 0.8478, prior_entropy: 0.9509, recall: 0.8478, relative_absolute_error: 0.5036, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3412, root_relative_squared_error: 0.7069, scimark_benchmark: 946.0795,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9014, f_measure: 0.8627, kappa: 0.703, kb_relative_information_score: 175.1289, mean_absolute_error: 0.2636, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8633, predictive_accuracy: 0.8641, prior_entropy: 0.9509, recall: 0.8641, relative_absolute_error: 0.5654, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.337, root_relative_squared_error: 0.6981, scimark_benchmark: 946.0783,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5478, f_measure: 0.5628, kappa: 0.1176, kb_relative_information_score: 96.0772, mean_absolute_error: 0.3342, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.7816, predictive_accuracy: 0.6658, prior_entropy: 0.9509, recall: 0.6658, relative_absolute_error: 0.717, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.5781, root_relative_squared_error: 1.1977, scimark_benchmark: 937.4428,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8169, f_measure: 0.8557, kappa: 0.6863, kb_relative_information_score: 188.6824, mean_absolute_error: 0.2441, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8595, predictive_accuracy: 0.8587, prior_entropy: 0.9509, recall: 0.8587, relative_absolute_error: 0.5237, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3519, root_relative_squared_error: 0.7291, scimark_benchmark: 947.5984,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8387, f_measure: 0.8228, kappa: 0.6151, kb_relative_information_score: 159.2835, mean_absolute_error: 0.279, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8248, predictive_accuracy: 0.8261, prior_entropy: 0.9509, recall: 0.8261, relative_absolute_error: 0.5985, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3753, root_relative_squared_error: 0.7775, scimark_benchmark: 908.3004,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8527, f_measure: 0.8275, kappa: 0.6247, kb_relative_information_score: 175.8384, mean_absolute_error: 0.2538, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8314, predictive_accuracy: 0.8315, prior_entropy: 0.9509, recall: 0.8315, relative_absolute_error: 0.5444, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3659, root_relative_squared_error: 0.758, scimark_benchmark: 943.3897,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8187, f_measure: 0.8486, kappa: 0.67, kb_relative_information_score: 190.9684, mean_absolute_error: 0.2398, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8571, predictive_accuracy: 0.8533, prior_entropy: 0.9509, recall: 0.8533, relative_absolute_error: 0.5143, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3522, root_relative_squared_error: 0.7296, scimark_benchmark: 949.3483,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8681, f_measure: 0.8217, kappa: 0.6145, kb_relative_information_score: 194.043, mean_absolute_error: 0.2267, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8216, predictive_accuracy: 0.8234, prior_entropy: 0.9509, recall: 0.8234, relative_absolute_error: 0.4863, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3649, root_relative_squared_error: 0.756, scimark_benchmark: 948.1981,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8876, f_measure: 0.8511, kappa: 0.6772, kb_relative_information_score: 194.7897, mean_absolute_error: 0.2341, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8525, predictive_accuracy: 0.8533, prior_entropy: 0.9509, recall: 0.8533, relative_absolute_error: 0.5022, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3413, root_relative_squared_error: 0.707, scimark_benchmark: 940.976,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7944, f_measure: 0.8095, kappa: 0.5905, kb_relative_information_score: 213.1571, mean_absolute_error: 0.1902, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8092, predictive_accuracy: 0.8098, prior_entropy: 0.9509, recall: 0.8098, relative_absolute_error: 0.4081, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4361, root_relative_squared_error: 0.9036, scimark_benchmark: 947.7946,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8479, f_measure: 0.8281, kappa: 0.6298, kb_relative_information_score: 186.1917, mean_absolute_error: 0.2365, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8277, predictive_accuracy: 0.8288, prior_entropy: 0.9509, recall: 0.8288, relative_absolute_error: 0.5074, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3764, root_relative_squared_error: 0.7798, scimark_benchmark: 927.5047,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8893, f_measure: 0.8453, kappa: 0.6642, kb_relative_information_score: 193.9445, mean_absolute_error: 0.2348, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8472, predictive_accuracy: 0.8478, prior_entropy: 0.9509, recall: 0.8478, relative_absolute_error: 0.5038, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3416, root_relative_squared_error: 0.7078, scimark_benchmark: 945.4325,

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