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OpenML
OpenML
Supervised Classification on ionosphere

Supervised Classification on ionosphere

Task 57 Supervised Classification ionosphere 1206 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • 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
Issue #Downvotes for this reason By


Metric:

1206 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9823, f_measure: 0.9339, kappa: 0.8553, kb_relative_information_score: 260.5845, mean_absolute_error: 0.1304, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9347, predictive_accuracy: 0.9345, prior_entropy: 0.9425, recall: 0.9345, relative_absolute_error: 0.2832, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2258, root_relative_squared_error: 0.4707,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9399, f_measure: 0.8218, kappa: 0.6051, kb_relative_information_score: 181.8955, mean_absolute_error: 0.2336, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8582, predictive_accuracy: 0.8348, prior_entropy: 0.9425, recall: 0.8348, relative_absolute_error: 0.5073, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.344, root_relative_squared_error: 0.717, scimark_benchmark: 945.9049,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9563, f_measure: 0.9194, kappa: 0.8236, kb_relative_information_score: 280.5349, mean_absolute_error: 0.0922, 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: 0.2003, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.258, root_relative_squared_error: 0.5377, scimark_benchmark: 947.2864,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9727, f_measure: 0.9103, kappa: 0.8029, kb_relative_information_score: 260.696, mean_absolute_error: 0.1228, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9127, predictive_accuracy: 0.9117, prior_entropy: 0.9425, recall: 0.9117, relative_absolute_error: 0.2667, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.253, root_relative_squared_error: 0.5273, scimark_benchmark: 941.8415,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9534, f_measure: 0.9157, kappa: 0.8143, kb_relative_information_score: 282.6886, mean_absolute_error: 0.0866, 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: 0.1882, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2794, root_relative_squared_error: 0.5824, scimark_benchmark: 895.8588,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8935, f_measure: 0.8736, kappa: 0.7206, kb_relative_information_score: 248.4158, mean_absolute_error: 0.133, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.882, predictive_accuracy: 0.8775, prior_entropy: 0.9425, recall: 0.8775, relative_absolute_error: 0.2887, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3266, root_relative_squared_error: 0.6809, scimark_benchmark: 939.9678,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9538, f_measure: 0.9127, kappa: 0.8076, kb_relative_information_score: 284.032, mean_absolute_error: 0.0845, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9177, predictive_accuracy: 0.9145, prior_entropy: 0.9425, recall: 0.9145, relative_absolute_error: 0.1836, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2802, root_relative_squared_error: 0.5841, scimark_benchmark: 945.7616,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8935, f_measure: 0.8736, kappa: 0.7206, kb_relative_information_score: 248.4158, mean_absolute_error: 0.133, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.882, predictive_accuracy: 0.8775, prior_entropy: 0.9425, recall: 0.8775, relative_absolute_error: 0.2887, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3266, root_relative_squared_error: 0.6809, scimark_benchmark: 938.8164,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9193, f_measure: 0.8826, kappa: 0.7406, kb_relative_information_score: 259.4538, mean_absolute_error: 0.116, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8906, predictive_accuracy: 0.886, prior_entropy: 0.9425, recall: 0.886, relative_absolute_error: 0.2519, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3266, root_relative_squared_error: 0.6808, scimark_benchmark: 941.8538,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9333, f_measure: 0.9454, kappa: 0.8805, kb_relative_information_score: 308.0515, mean_absolute_error: 0.0541, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9463, 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,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9195, f_measure: 0.8044, kappa: 0.5669, kb_relative_information_score: 171.3926, mean_absolute_error: 0.2448, 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: 0.5317, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.376, root_relative_squared_error: 0.7839, scimark_benchmark: 948.0261,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8538, f_measure: 0.8756, kappa: 0.7267, kb_relative_information_score: 254.1134, mean_absolute_error: 0.1225, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8773, 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: 947.6879,
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: 920.5349,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9111, f_measure: 0.8334, kappa: 0.6305, kb_relative_information_score: 224.9372, mean_absolute_error: 0.1628, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8591, predictive_accuracy: 0.8433, prior_entropy: 0.9425, recall: 0.8433, relative_absolute_error: 0.3536, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.338, root_relative_squared_error: 0.7045, scimark_benchmark: 946.9006,
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: 925.6711,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9214, f_measure: 0.9075, kappa: 0.8049, kb_relative_information_score: 276.5876, mean_absolute_error: 0.094, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9199, 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: 950.0118,
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,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9306, f_measure: 0.9035, kappa: 0.7872, kb_relative_information_score: 272.2932, mean_absolute_error: 0.1016, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9102, predictive_accuracy: 0.906, prior_entropy: 0.9425, recall: 0.906, relative_absolute_error: 0.2206, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2836, root_relative_squared_error: 0.5911, scimark_benchmark: 947.6811,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8868, f_measure: 0.8786, kappa: 0.7335, kb_relative_information_score: 216.1642, mean_absolute_error: 0.1896, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.88, predictive_accuracy: 0.8803, prior_entropy: 0.9425, recall: 0.8803, relative_absolute_error: 0.4118, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3149, root_relative_squared_error: 0.6565, scimark_benchmark: 886.4854,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6667, f_measure: 0.7197, kappa: 0.3906, kb_relative_information_score: 161.969, mean_absolute_error: 0.2393, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8257, predictive_accuracy: 0.7607, prior_entropy: 0.9425, recall: 0.7607, relative_absolute_error: 0.5197, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.4892, root_relative_squared_error: 1.0198,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.965, f_measure: 0.9165, kappa: 0.817, kb_relative_information_score: 246.5338, mean_absolute_error: 0.1481, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9176, predictive_accuracy: 0.9174, prior_entropy: 0.9425, recall: 0.9174, relative_absolute_error: 0.3216, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2563, root_relative_squared_error: 0.5342, scimark_benchmark: 947.4785,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8637, f_measure: 0.8916, kappa: 0.7605, kb_relative_information_score: 267.5979, mean_absolute_error: 0.1054, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8992, predictive_accuracy: 0.8946, prior_entropy: 0.9425, recall: 0.8946, relative_absolute_error: 0.2289, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3247, root_relative_squared_error: 0.6768, scimark_benchmark: 924.5928,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9346, f_measure: 0.9099, kappa: 0.8015, kb_relative_information_score: 233.5829, mean_absolute_error: 0.1659, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9142, predictive_accuracy: 0.9117, prior_entropy: 0.9425, recall: 0.9117, relative_absolute_error: 0.3603, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2749, root_relative_squared_error: 0.573, scimark_benchmark: 923.8745,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.966, f_measure: 0.9194, kappa: 0.8236, kb_relative_information_score: 247.2981, mean_absolute_error: 0.147, 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: 0.3193, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2549, root_relative_squared_error: 0.5314, scimark_benchmark: 948.5654,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9806, f_measure: 0.9366, kappa: 0.8609, kb_relative_information_score: 260.9688, mean_absolute_error: 0.1299, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9383, predictive_accuracy: 0.9373, prior_entropy: 0.9425, recall: 0.9373, relative_absolute_error: 0.2822, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2263, root_relative_squared_error: 0.4718, scimark_benchmark: 948.352,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8834, f_measure: 0.8904, kappa: 0.7597, kb_relative_information_score: 258.0173, mean_absolute_error: 0.1214, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8914, predictive_accuracy: 0.8917, prior_entropy: 0.9425, recall: 0.8917, relative_absolute_error: 0.2636, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3183, root_relative_squared_error: 0.6636, scimark_benchmark: 948.4636,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9297, f_measure: 0.8328, kappa: 0.6291, kb_relative_information_score: 203.0794, mean_absolute_error: 0.1945, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8616, predictive_accuracy: 0.8433, prior_entropy: 0.9425, recall: 0.8433, relative_absolute_error: 0.4225, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3619, root_relative_squared_error: 0.7543, scimark_benchmark: 917.3825,
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: 883.8284,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9648, f_measure: 0.9163, kappa: 0.8163, kb_relative_information_score: 247.1265, mean_absolute_error: 0.1471, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.918, predictive_accuracy: 0.9174, prior_entropy: 0.9425, recall: 0.9174, relative_absolute_error: 0.3195, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2557, root_relative_squared_error: 0.533,
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,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8835, f_measure: 0.9068, kappa: 0.7947, kb_relative_information_score: 278.835, mean_absolute_error: 0.0912, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9117, predictive_accuracy: 0.9088, prior_entropy: 0.9425, recall: 0.9088, relative_absolute_error: 0.198, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3019, root_relative_squared_error: 0.6294,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9672, f_measure: 0.9395, kappa: 0.8675, kb_relative_information_score: 290.6521, mean_absolute_error: 0.0812, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9409, predictive_accuracy: 0.9402, prior_entropy: 0.9425, recall: 0.9402, relative_absolute_error: 0.1763, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2304, root_relative_squared_error: 0.4803, scimark_benchmark: 946.5452,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8651, f_measure: 0.8949, kappa: 0.7682, kb_relative_information_score: 243.7687, mean_absolute_error: 0.1379, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9006, predictive_accuracy: 0.8974, prior_entropy: 0.9425, recall: 0.8974, relative_absolute_error: 0.2995, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3372, root_relative_squared_error: 0.7028, scimark_benchmark: 945.4199,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8733, f_measure: 0.898, kappa: 0.7751, kb_relative_information_score: 272.0928, mean_absolute_error: 0.0997, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9031, predictive_accuracy: 0.9003, prior_entropy: 0.9425, recall: 0.9003, relative_absolute_error: 0.2166, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3158, root_relative_squared_error: 0.6583, scimark_benchmark: 943.1059,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9523, f_measure: 0.9127, kappa: 0.8076, kb_relative_information_score: 252.4981, mean_absolute_error: 0.1363, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9177, predictive_accuracy: 0.9145, prior_entropy: 0.9425, recall: 0.9145, relative_absolute_error: 0.296, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2648, root_relative_squared_error: 0.5519, scimark_benchmark: 946.2016,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9379, f_measure: 0.9323, kappa: 0.855, kb_relative_information_score: 296.8144, mean_absolute_error: 0.0684, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9361, 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: 947.8485,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9497, f_measure: 0.9336, kappa: 0.8543, kb_relative_information_score: 259.9607, mean_absolute_error: 0.1254, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9356, predictive_accuracy: 0.9345, prior_entropy: 0.9425, recall: 0.9345, relative_absolute_error: 0.2722, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2578, root_relative_squared_error: 0.5375, scimark_benchmark: 946.2435,
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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,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9306, f_measure: 0.83, kappa: 0.6231, kb_relative_information_score: 206.3711, mean_absolute_error: 0.1892, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8569, predictive_accuracy: 0.8405, prior_entropy: 0.9425, recall: 0.8405, relative_absolute_error: 0.411, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3581, root_relative_squared_error: 0.7465, scimark_benchmark: 920.8725,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9237, f_measure: 0.9394, kappa: 0.867, kb_relative_information_score: 303.5567, mean_absolute_error: 0.0598, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9415, predictive_accuracy: 0.9402, prior_entropy: 0.9425, recall: 0.9402, relative_absolute_error: 0.1299, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2446, root_relative_squared_error: 0.5099, scimark_benchmark: 946.3792,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9237, f_measure: 0.9394, kappa: 0.867, kb_relative_information_score: 303.5567, mean_absolute_error: 0.0598, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9415, predictive_accuracy: 0.9402, prior_entropy: 0.9425, recall: 0.9402, relative_absolute_error: 0.1299, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2446, root_relative_squared_error: 0.5099, scimark_benchmark: 949.4424,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5198, f_measure: 0.5326, kappa: 0.0503, kb_relative_information_score: 78.8143, mean_absolute_error: 0.3447, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.7758, predictive_accuracy: 0.6553, prior_entropy: 0.9425, recall: 0.6553, relative_absolute_error: 0.7487, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.5871, root_relative_squared_error: 1.224, scimark_benchmark: 947.4251,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.827, f_measure: 0.8587, kappa: 0.6876, kb_relative_information_score: 242.8763, mean_absolute_error: 0.1368, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8671, predictive_accuracy: 0.8632, prior_entropy: 0.9425, recall: 0.8632, relative_absolute_error: 0.297, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3698, root_relative_squared_error: 0.7709, scimark_benchmark: 917.862,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9493, f_measure: 0.9052, kappa: 0.7925, kb_relative_information_score: 248.4463, mean_absolute_error: 0.1407, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9057, predictive_accuracy: 0.906, prior_entropy: 0.9425, recall: 0.906, relative_absolute_error: 0.3057, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2777, root_relative_squared_error: 0.5789, scimark_benchmark: 944.1887,

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