OpenML
Supervised Classification on ionosphere

Supervised Classification on ionosphere

Task 57 Supervised Classification ionosphere 1206 runs submitted
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  • basic mythbusting mythbusting_1 study_1 study_107 study_123 study_15 study_20 study_29 study_30 study_41 study_50 study_7 study_73 under100k under1m
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1206 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9831, f_measure: 0.928, kappa: 0.8422, kb_relative_information_score: 260.8688, mean_absolute_error: 0.1298, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9293, predictive_accuracy: 0.9288, prior_entropy: 0.9425, recall: 0.9288, relative_absolute_error: 0.2818, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2251, root_relative_squared_error: 0.4692, scimark_benchmark: 947.82,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5375, f_measure: 0.5607, kappa: 0.0937, kb_relative_information_score: 87.804, mean_absolute_error: 0.3333, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.7487, predictive_accuracy: 0.6667, prior_entropy: 0.9425, recall: 0.6667, relative_absolute_error: 0.7239, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.5774, root_relative_squared_error: 1.2036, scimark_benchmark: 921.7378,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8997, f_measure: 0.8921, kappa: 0.7622, kb_relative_information_score: 249.3137, mean_absolute_error: 0.1387, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8971, predictive_accuracy: 0.8946, prior_entropy: 0.9425, recall: 0.8946, relative_absolute_error: 0.3012, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2963, root_relative_squared_error: 0.6176, scimark_benchmark: 944.2214,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8864, f_measure: 0.8962, kappa: 0.7724, kb_relative_information_score: 263.2194, mean_absolute_error: 0.1144, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8973, predictive_accuracy: 0.8974, prior_entropy: 0.9425, recall: 0.8974, relative_absolute_error: 0.2484, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3106, root_relative_squared_error: 0.6475, scimark_benchmark: 946.8722,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7294, f_measure: 0.7701, kappa: 0.4904, kb_relative_information_score: 177.701, mean_absolute_error: 0.2194, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.7799, predictive_accuracy: 0.7806, prior_entropy: 0.9425, recall: 0.7806, relative_absolute_error: 0.4764, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.4684, root_relative_squared_error: 0.9764, scimark_benchmark: 917.3739,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9198, f_measure: 0.8367, kappa: 0.6379, kb_relative_information_score: 207.855, mean_absolute_error: 0.1874, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8613, predictive_accuracy: 0.8462, prior_entropy: 0.9425, recall: 0.8462, relative_absolute_error: 0.4069, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3572, root_relative_squared_error: 0.7447, scimark_benchmark: 915.0311,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8758, f_measure: 0.886, kappa: 0.7485, kb_relative_information_score: 245.0274, mean_absolute_error: 0.1437, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.892, predictive_accuracy: 0.8889, prior_entropy: 0.9425, recall: 0.8889, relative_absolute_error: 0.312, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3164, root_relative_squared_error: 0.6596, scimark_benchmark: 917.7669,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.91, f_measure: 0.9303, kappa: 0.8466, kb_relative_information_score: 296.8144, mean_absolute_error: 0.0684, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9346, predictive_accuracy: 0.9316, prior_entropy: 0.9425, recall: 0.9316, relative_absolute_error: 0.1485, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2615, root_relative_squared_error: 0.5451, scimark_benchmark: 947.4464,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9276, f_measure: 0.9423, kappa: 0.8735, kb_relative_information_score: 305.8041, mean_absolute_error: 0.057, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9441, predictive_accuracy: 0.943, prior_entropy: 0.9425, recall: 0.943, relative_absolute_error: 0.1237, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2387, root_relative_squared_error: 0.4976, scimark_benchmark: 928.6347,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9081, f_measure: 0.8909, kappa: 0.7717, kb_relative_information_score: 263.1031, mean_absolute_error: 0.1111, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9087, predictive_accuracy: 0.8889, prior_entropy: 0.9425, recall: 0.8889, relative_absolute_error: 0.2413, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3333, root_relative_squared_error: 0.6949, scimark_benchmark: 948.0065,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8756, f_measure: 0.8971, kappa: 0.7756, kb_relative_information_score: 233.2982, mean_absolute_error: 0.1657, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8969, predictive_accuracy: 0.8974, prior_entropy: 0.9425, recall: 0.8974, relative_absolute_error: 0.3598, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2975, root_relative_squared_error: 0.6201, scimark_benchmark: 948.7762,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8864, f_measure: 0.8962, kappa: 0.7724, kb_relative_information_score: 263.2194, mean_absolute_error: 0.1144, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8973, predictive_accuracy: 0.8974, prior_entropy: 0.9425, recall: 0.8974, relative_absolute_error: 0.2484, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3106, root_relative_squared_error: 0.6475, scimark_benchmark: 872.6703,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9657, f_measure: 0.9194, kappa: 0.8236, kb_relative_information_score: 246.0793, mean_absolute_error: 0.1486, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9203, predictive_accuracy: 0.9202, prior_entropy: 0.9425, recall: 0.9202, relative_absolute_error: 0.3227, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2559, root_relative_squared_error: 0.5335, scimark_benchmark: 940.4396,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.933, f_measure: 0.9241, kappa: 0.8382, kb_relative_information_score: 290.0721, mean_absolute_error: 0.0769, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9306, predictive_accuracy: 0.9231, prior_entropy: 0.9425, recall: 0.9231, relative_absolute_error: 0.1671, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2774, root_relative_squared_error: 0.5782, scimark_benchmark: 946.3939,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9179, f_measure: 0.8467, kappa: 0.6599, kb_relative_information_score: 215.8456, mean_absolute_error: 0.1753, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.868, predictive_accuracy: 0.8547, prior_entropy: 0.9425, recall: 0.8547, relative_absolute_error: 0.3807, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3501, root_relative_squared_error: 0.7299, scimark_benchmark: 919.1541,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9298, f_measure: 0.8291, kappa: 0.6394, kb_relative_information_score: 214.0987, mean_absolute_error: 0.1726, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8417, predictive_accuracy: 0.8262, prior_entropy: 0.9425, recall: 0.8262, relative_absolute_error: 0.3748, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.392, root_relative_squared_error: 0.8172, scimark_benchmark: 947.3932,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8521, f_measure: 0.8753, kappa: 0.7257, kb_relative_information_score: 254.1134, mean_absolute_error: 0.1225, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8777, predictive_accuracy: 0.8775, prior_entropy: 0.9425, recall: 0.8775, relative_absolute_error: 0.2661, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.35, root_relative_squared_error: 0.7296, scimark_benchmark: 946.865,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.875, f_measure: 0.8932, kappa: 0.7656, kb_relative_information_score: 257.195, mean_absolute_error: 0.1241, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8945, predictive_accuracy: 0.8946, prior_entropy: 0.9425, recall: 0.8946, relative_absolute_error: 0.2695, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3126, root_relative_squared_error: 0.6516, scimark_benchmark: 912.3079,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9117, f_measure: 0.9305, kappa: 0.8472, kb_relative_information_score: 296.8144, mean_absolute_error: 0.0684, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9337, predictive_accuracy: 0.9316, prior_entropy: 0.9425, recall: 0.9316, relative_absolute_error: 0.1485, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2615, root_relative_squared_error: 0.5451, scimark_benchmark: 947.5852,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9592, f_measure: 0.9311, kappa: 0.8493, kb_relative_information_score: 235.0541, mean_absolute_error: 0.1706, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9316, predictive_accuracy: 0.9316, prior_entropy: 0.9425, recall: 0.9316, relative_absolute_error: 0.3705, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2531, root_relative_squared_error: 0.5275, scimark_benchmark: 924.1561,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9236, f_measure: 0.9213, kappa: 0.8265, kb_relative_information_score: 278.9551, mean_absolute_error: 0.096, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9272, predictive_accuracy: 0.9231, prior_entropy: 0.9425, recall: 0.9231, relative_absolute_error: 0.2084, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2557, root_relative_squared_error: 0.533, scimark_benchmark: 945.9986,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8813, f_measure: 0.9041, kappa: 0.7887, kb_relative_information_score: 276.5876, mean_absolute_error: 0.094, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9082, predictive_accuracy: 0.906, prior_entropy: 0.9425, recall: 0.906, relative_absolute_error: 0.2042, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3066, root_relative_squared_error: 0.6392, scimark_benchmark: 947.8468,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9571, f_measure: 0.9157, kappa: 0.8143, kb_relative_information_score: 268.601, mean_absolute_error: 0.1105, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9202, predictive_accuracy: 0.9174, prior_entropy: 0.9425, recall: 0.9174, relative_absolute_error: 0.2399, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2551, root_relative_squared_error: 0.5317, scimark_benchmark: 944.9429,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.799, f_measure: 0.828, kappa: 0.6209, kb_relative_information_score: 218.1546, mean_absolute_error: 0.1681, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8308, predictive_accuracy: 0.8319, prior_entropy: 0.9425, recall: 0.8319, relative_absolute_error: 0.3651, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.41, root_relative_squared_error: 0.8547, scimark_benchmark: 947.9821,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.877, f_measure: 0.8624, kappa: 0.695, kb_relative_information_score: 237.6577, mean_absolute_error: 0.146, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8813, predictive_accuracy: 0.8689, prior_entropy: 0.9425, recall: 0.8689, relative_absolute_error: 0.3172, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3359, root_relative_squared_error: 0.7003, scimark_benchmark: 945.5652,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9373, f_measure: 0.9483, kappa: 0.887, kb_relative_information_score: 310.299, mean_absolute_error: 0.0513, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.949, predictive_accuracy: 0.9487, prior_entropy: 0.9425, recall: 0.9487, relative_absolute_error: 0.1114, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2265, root_relative_squared_error: 0.4721, scimark_benchmark: 922.5645,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8864, f_measure: 0.8962, kappa: 0.7724, kb_relative_information_score: 263.2194, mean_absolute_error: 0.1144, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8973, predictive_accuracy: 0.8974, prior_entropy: 0.9425, recall: 0.8974, relative_absolute_error: 0.2484, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3106, root_relative_squared_error: 0.6475, scimark_benchmark: 912.1911,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9368, f_measure: 0.9456, kappa: 0.8813, kb_relative_information_score: 308.0515, mean_absolute_error: 0.0541, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9458, predictive_accuracy: 0.9459, prior_entropy: 0.9425, recall: 0.9459, relative_absolute_error: 0.1176, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2327, root_relative_squared_error: 0.485, scimark_benchmark: 946.5508,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9236, f_measure: 0.9213, kappa: 0.8265, kb_relative_information_score: 278.9551, mean_absolute_error: 0.096, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9272, predictive_accuracy: 0.9231, prior_entropy: 0.9425, recall: 0.9231, relative_absolute_error: 0.2084, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2557, root_relative_squared_error: 0.533, scimark_benchmark: 944.7529,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9667, f_measure: 0.9222, kappa: 0.8296, kb_relative_information_score: 247.6553, mean_absolute_error: 0.1465, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9234, predictive_accuracy: 0.9231, prior_entropy: 0.9425, recall: 0.9231, relative_absolute_error: 0.3181, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2548, root_relative_squared_error: 0.5312,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.879, f_measure: 0.8943, kappa: 0.7697, kb_relative_information_score: 233.3476, mean_absolute_error: 0.1649, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8942, predictive_accuracy: 0.8946, prior_entropy: 0.9425, recall: 0.8946, relative_absolute_error: 0.358, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.299, root_relative_squared_error: 0.6233, scimark_benchmark: 943.4904,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5238, f_measure: 0.5387, kappa: 0.0602, kb_relative_information_score: 81.0618, mean_absolute_error: 0.3419, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.777, predictive_accuracy: 0.6581, prior_entropy: 0.9425, recall: 0.6581, relative_absolute_error: 0.7425, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.5847, root_relative_squared_error: 1.2189, scimark_benchmark: 948.5321,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8908, f_measure: 0.8874, kappa: 0.753, kb_relative_information_score: 229.3455, mean_absolute_error: 0.1698, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8887, predictive_accuracy: 0.8889, prior_entropy: 0.9425, recall: 0.8889, relative_absolute_error: 0.3688, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.308, root_relative_squared_error: 0.6421, scimark_benchmark: 919.9961,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9652, f_measure: 0.9137, kappa: 0.811, kb_relative_information_score: 246.5224, mean_absolute_error: 0.148, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9145, predictive_accuracy: 0.9145, prior_entropy: 0.9425, recall: 0.9145, relative_absolute_error: 0.3213, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2566, root_relative_squared_error: 0.5349, scimark_benchmark: 947.1061,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9578, f_measure: 0.9107, kappa: 0.8043, kb_relative_information_score: 265.6927, mean_absolute_error: 0.1152, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9117, predictive_accuracy: 0.9117, prior_entropy: 0.9425, recall: 0.9117, relative_absolute_error: 0.2503, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2574, root_relative_squared_error: 0.5365,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9119, f_measure: 0.896, kappa: 0.7716, kb_relative_information_score: 256.7901, mean_absolute_error: 0.1267, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8977, predictive_accuracy: 0.8974, prior_entropy: 0.9425, recall: 0.8974, relative_absolute_error: 0.2752, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.291, root_relative_squared_error: 0.6066, scimark_benchmark: 915.2047,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9433, f_measure: 0.9433, kappa: 0.8775, kb_relative_information_score: 305.8041, mean_absolute_error: 0.057, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9442, predictive_accuracy: 0.943, prior_entropy: 0.9425, recall: 0.943, relative_absolute_error: 0.1237, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2387, root_relative_squared_error: 0.4976, scimark_benchmark: 946.7355,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5008, kb_relative_information_score: 67.5772, mean_absolute_error: 0.359, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.4109, predictive_accuracy: 0.641, prior_entropy: 0.9425, recall: 0.641, relative_absolute_error: 0.7796, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.5991, root_relative_squared_error: 1.249, scimark_benchmark: 948.8963,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8864, f_measure: 0.8962, kappa: 0.7724, kb_relative_information_score: 263.2194, mean_absolute_error: 0.1144, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8973, predictive_accuracy: 0.8974, prior_entropy: 0.9425, recall: 0.8974, relative_absolute_error: 0.2484, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3106, root_relative_squared_error: 0.6475, scimark_benchmark: 914.0867,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8543, f_measure: 0.878, kappa: 0.7316, kb_relative_information_score: 256.3608, mean_absolute_error: 0.1197, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.881, predictive_accuracy: 0.8803, prior_entropy: 0.9425, recall: 0.8803, relative_absolute_error: 0.2599, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3459, root_relative_squared_error: 0.7211, scimark_benchmark: 949.3657,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5238, f_measure: 0.5387, kappa: 0.0602, kb_relative_information_score: 81.0618, mean_absolute_error: 0.3419, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.777, predictive_accuracy: 0.6581, prior_entropy: 0.9425, recall: 0.6581, relative_absolute_error: 0.7425, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.5847, root_relative_squared_error: 1.2189, scimark_benchmark: 927.2877,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8327, f_measure: 0.8622, kappa: 0.6958, kb_relative_information_score: 245.1237, mean_absolute_error: 0.1339, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8686, predictive_accuracy: 0.8661, prior_entropy: 0.9425, recall: 0.8661, relative_absolute_error: 0.2908, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3659, root_relative_squared_error: 0.7628, scimark_benchmark: 947.2938,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8864, f_measure: 0.8962, kappa: 0.7724, kb_relative_information_score: 263.2194, mean_absolute_error: 0.1144, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8973, predictive_accuracy: 0.8974, prior_entropy: 0.9425, recall: 0.8974, relative_absolute_error: 0.2484, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3106, root_relative_squared_error: 0.6475, scimark_benchmark: 948.3241,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9707, f_measure: 0.9247, kappa: 0.8344, kb_relative_information_score: 295.078, mean_absolute_error: 0.0722, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9278, predictive_accuracy: 0.9259, prior_entropy: 0.9425, recall: 0.9259, relative_absolute_error: 0.1568, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2345, root_relative_squared_error: 0.4887, scimark_benchmark: 940.7591,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5008, kb_relative_information_score: 67.5772, mean_absolute_error: 0.359, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.4109, predictive_accuracy: 0.641, prior_entropy: 0.9425, recall: 0.641, relative_absolute_error: 0.7796, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.5991, root_relative_squared_error: 1.249, scimark_benchmark: 935.3937,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8969, f_measure: 0.8665, kappa: 0.7044, kb_relative_information_score: 231.5664, mean_absolute_error: 0.1537, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8799, predictive_accuracy: 0.8718, prior_entropy: 0.9425, recall: 0.8718, relative_absolute_error: 0.3338, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3366, root_relative_squared_error: 0.7017, scimark_benchmark: 947.4967,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8346, f_measure: 0.8716, kappa: 0.7154, kb_relative_information_score: 254.1134, mean_absolute_error: 0.1225, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.89, predictive_accuracy: 0.8775, prior_entropy: 0.9425, recall: 0.8775, relative_absolute_error: 0.2661, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.35, root_relative_squared_error: 0.7296, scimark_benchmark: 946.4879,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9236, f_measure: 0.9213, kappa: 0.8265, kb_relative_information_score: 278.9551, mean_absolute_error: 0.096, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9272, predictive_accuracy: 0.9231, prior_entropy: 0.9425, recall: 0.9231, relative_absolute_error: 0.2084, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2557, root_relative_squared_error: 0.533, scimark_benchmark: 946.0349,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7311, f_measure: 0.8044, kappa: 0.5669, kb_relative_information_score: 151.5062, mean_absolute_error: 0.2753, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.848, predictive_accuracy: 0.8205, prior_entropy: 0.9425, recall: 0.8205, relative_absolute_error: 0.598, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3784, root_relative_squared_error: 0.7889, scimark_benchmark: 947.939,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9701, f_measure: 0.9172, kappa: 0.8195, kb_relative_information_score: 259.861, mean_absolute_error: 0.1262, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9171, predictive_accuracy: 0.9174, prior_entropy: 0.9425, recall: 0.9174, relative_absolute_error: 0.2741, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2457, root_relative_squared_error: 0.5122, scimark_benchmark: 912.9476,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8604, f_measure: 0.8722, kappa: 0.7188, kb_relative_information_score: 240.7167, mean_absolute_error: 0.144, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.875, predictive_accuracy: 0.8746, prior_entropy: 0.9425, recall: 0.8746, relative_absolute_error: 0.3127, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3254, root_relative_squared_error: 0.6783, scimark_benchmark: 916.0284,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8848, f_measure: 0.8957, kappa: 0.7707, kb_relative_information_score: 247.4029, mean_absolute_error: 0.1415, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8982, predictive_accuracy: 0.8974, prior_entropy: 0.9425, recall: 0.8974, relative_absolute_error: 0.3073, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3079, root_relative_squared_error: 0.6419, scimark_benchmark: 941.4166,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4849, f_measure: 0.5008, kb_relative_information_score: -0.2061, mean_absolute_error: 0.4605, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.4109, predictive_accuracy: 0.641, prior_entropy: 0.9425, recall: 0.641, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.4797, root_relative_squared_error: 1.0001, scimark_benchmark: 923.9281,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4849, f_measure: 0.5008, kb_relative_information_score: -0.2061, mean_absolute_error: 0.4605, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.4109, predictive_accuracy: 0.641, prior_entropy: 0.9425, recall: 0.641, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.4797, root_relative_squared_error: 1.0001, scimark_benchmark: 940.3824,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9537, f_measure: 0.9054, kappa: 0.7932, kb_relative_information_score: 242.6749, mean_absolute_error: 0.151, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9055, predictive_accuracy: 0.906, prior_entropy: 0.9425, recall: 0.906, relative_absolute_error: 0.3279, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2688, root_relative_squared_error: 0.5604, scimark_benchmark: 2007.7498,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8702, f_measure: 0.8884, kappa: 0.7564, kb_relative_information_score: 238.0036, mean_absolute_error: 0.1548, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8883, predictive_accuracy: 0.8889, prior_entropy: 0.9425, recall: 0.8889, relative_absolute_error: 0.3362, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3135, root_relative_squared_error: 0.6535, scimark_benchmark: 2010.5429,

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