OpenML
Supervised Classification on diabetes

Supervised Classification on diabetes

Task 37 Supervised Classification diabetes 131682 runs submitted
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  • at2 basic mythbusting mythbusting_1 OpenML-CC18 OpenML100 study_1 study_107 study_123 study_14 study_15 study_20 study_29 study_30 study_41 study_7 study_70 study_73 study_98 study_99 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7729, build_cpu_time: 0.6062, build_memory: 222703515.9271, f_measure: 0.7087, kappa: 0.3571, kb_relative_information_score: 264.1062, mean_absolute_error: 0.286, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7079, predictive_accuracy: 0.7096, prior_entropy: 0.9335, recall: 0.7096, relative_absolute_error: 0.6292, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4925, root_relative_squared_error: 1.0332, scimark_benchmark: 937.4026,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8336, f_measure: 0.7586, kappa: 0.4603, kb_relative_information_score: 247.5509, mean_absolute_error: 0.3143, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7586, predictive_accuracy: 0.7643, prior_entropy: 0.9335, recall: 0.7643, relative_absolute_error: 0.6915, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3952, root_relative_squared_error: 0.829, scimark_benchmark: 946.6613,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7974, f_measure: 0.7417, kappa: 0.42, kb_relative_information_score: 319.0493, mean_absolute_error: 0.2579, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7442, predictive_accuracy: 0.7513, prior_entropy: 0.9335, recall: 0.7513, relative_absolute_error: 0.5674, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4609, root_relative_squared_error: 0.967, scimark_benchmark: 942.7144,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7896, f_measure: 0.7577, kappa: 0.455, kb_relative_information_score: 254.7996, mean_absolute_error: 0.3129, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7636, predictive_accuracy: 0.7682, prior_entropy: 0.9335, recall: 0.7682, relative_absolute_error: 0.6885, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4167, root_relative_squared_error: 0.8743, scimark_benchmark: 935.001,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8031, f_measure: 0.7394, kappa: 0.415, kb_relative_information_score: 221.3922, mean_absolute_error: 0.3274, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7413, predictive_accuracy: 0.7487, prior_entropy: 0.9335, recall: 0.7487, relative_absolute_error: 0.7204, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4115, root_relative_squared_error: 0.8634, scimark_benchmark: 941.4701,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7886, f_measure: 0.7372, kappa: 0.4221, kb_relative_information_score: 286.9851, mean_absolute_error: 0.2763, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7374, predictive_accuracy: 0.737, prior_entropy: 0.9335, recall: 0.737, relative_absolute_error: 0.6079, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4756, root_relative_squared_error: 0.9978, scimark_benchmark: 948.9036,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7368, f_measure: 0.6988, kappa: 0.3363, kb_relative_information_score: 232.3889, mean_absolute_error: 0.3048, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.6984, predictive_accuracy: 0.6992, prior_entropy: 0.9335, recall: 0.6992, relative_absolute_error: 0.6706, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5322, root_relative_squared_error: 1.1166, scimark_benchmark: 946.8336,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8352, f_measure: 0.7654, kappa: 0.4769, kb_relative_information_score: 253.4157, mean_absolute_error: 0.3099, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7647, predictive_accuracy: 0.7695, prior_entropy: 0.9335, recall: 0.7695, relative_absolute_error: 0.6818, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3942, root_relative_squared_error: 0.8269, scimark_benchmark: 948.8808,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7817, f_measure: 0.7415, kappa: 0.4237, kb_relative_information_score: 303.3968, mean_absolute_error: 0.2682, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7402, predictive_accuracy: 0.7461, prior_entropy: 0.9335, recall: 0.7461, relative_absolute_error: 0.5901, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4539, root_relative_squared_error: 0.9523, scimark_benchmark: 949.3309,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6551, f_measure: 0.6863, kappa: 0.31, kb_relative_information_score: 215.9197, mean_absolute_error: 0.3138, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.6865, predictive_accuracy: 0.6862, prior_entropy: 0.9335, recall: 0.6862, relative_absolute_error: 0.6904, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5602, root_relative_squared_error: 1.1753, scimark_benchmark: 925.9152,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8031, f_measure: 0.761, kappa: 0.4666, kb_relative_information_score: 270.7828, mean_absolute_error: 0.2969, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7604, predictive_accuracy: 0.7656, prior_entropy: 0.9335, recall: 0.7656, relative_absolute_error: 0.6532, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4162, root_relative_squared_error: 0.8732, scimark_benchmark: 931.0881,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.802, f_measure: 0.7474, kappa: 0.4376, kb_relative_information_score: 246.4961, mean_absolute_error: 0.3093, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7461, predictive_accuracy: 0.7513, prior_entropy: 0.9335, recall: 0.7513, relative_absolute_error: 0.6805, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4164, root_relative_squared_error: 0.8736, scimark_benchmark: 940.6768,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7857, f_measure: 0.7383, kappa: 0.4192, kb_relative_information_score: 308.7158, mean_absolute_error: 0.2618, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7368, predictive_accuracy: 0.7409, prior_entropy: 0.9335, recall: 0.7409, relative_absolute_error: 0.5761, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.487, root_relative_squared_error: 1.0217, scimark_benchmark: 925.3625,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8356, f_measure: 0.7571, kappa: 0.4568, kb_relative_information_score: 249.6671, mean_absolute_error: 0.313, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7572, predictive_accuracy: 0.763, prior_entropy: 0.9335, recall: 0.763, relative_absolute_error: 0.6887, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3942, root_relative_squared_error: 0.827, scimark_benchmark: 929.6271,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7708, f_measure: 0.7109, kappa: 0.3552, kb_relative_information_score: 217.4307, mean_absolute_error: 0.3215, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7089, predictive_accuracy: 0.7161, prior_entropy: 0.9335, recall: 0.7161, relative_absolute_error: 0.7073, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4389, root_relative_squared_error: 0.9209, scimark_benchmark: 926.8486,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8126, f_measure: 0.7553, kappa: 0.4552, kb_relative_information_score: 253.9609, mean_absolute_error: 0.3064, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7542, predictive_accuracy: 0.7591, prior_entropy: 0.9335, recall: 0.7591, relative_absolute_error: 0.6741, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4105, root_relative_squared_error: 0.8613, scimark_benchmark: 942.7876,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7462, f_measure: 0.7598, kappa: 0.4642, kb_relative_information_score: 352.5398, mean_absolute_error: 0.2362, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7591, predictive_accuracy: 0.7643, prior_entropy: 0.9335, recall: 0.7643, relative_absolute_error: 0.5197, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4827, root_relative_squared_error: 1.0127, scimark_benchmark: 929.0467,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6725, f_measure: 0.7006, kappa: 0.3363, kb_relative_information_score: 244.9883, mean_absolute_error: 0.2975, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.6988, predictive_accuracy: 0.7031, prior_entropy: 0.9335, recall: 0.7031, relative_absolute_error: 0.6545, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5441, root_relative_squared_error: 1.1415, scimark_benchmark: 936.8663,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7703, f_measure: 0.7315, kappa: 0.4041, kb_relative_information_score: 269.1919, mean_absolute_error: 0.2891, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.73, predictive_accuracy: 0.7344, prior_entropy: 0.9335, recall: 0.7344, relative_absolute_error: 0.636, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4632, root_relative_squared_error: 0.9718,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8111, f_measure: 0.7507, kappa: 0.4479, kb_relative_information_score: 267.8873, mean_absolute_error: 0.295, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7496, predictive_accuracy: 0.7526, prior_entropy: 0.9335, recall: 0.7526, relative_absolute_error: 0.6492, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4165, root_relative_squared_error: 0.8737, scimark_benchmark: 925.8511,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8202, f_measure: 0.7497, kappa: 0.4409, kb_relative_information_score: 329.9107, mean_absolute_error: 0.2506, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7491, predictive_accuracy: 0.7552, prior_entropy: 0.9335, recall: 0.7552, relative_absolute_error: 0.5513, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4546, root_relative_squared_error: 0.9538, scimark_benchmark: 923.9245,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7274, f_measure: 0.687, kappa: 0.2946, kb_relative_information_score: 209.9406, mean_absolute_error: 0.327, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.6956, predictive_accuracy: 0.7083, prior_entropy: 0.9335, recall: 0.7083, relative_absolute_error: 0.7196, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4567, root_relative_squared_error: 0.9581, scimark_benchmark: 929.0848,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7819, f_measure: 0.7127, kappa: 0.3526, kb_relative_information_score: 167.0349, mean_absolute_error: 0.3645, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7265, predictive_accuracy: 0.7331, prior_entropy: 0.9335, recall: 0.7331, relative_absolute_error: 0.802, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4208, root_relative_squared_error: 0.8829,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8143, f_measure: 0.7574, kappa: 0.4578, kb_relative_information_score: 254.6969, mean_absolute_error: 0.3062, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7573, predictive_accuracy: 0.763, prior_entropy: 0.9335, recall: 0.763, relative_absolute_error: 0.6736, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4081, root_relative_squared_error: 0.8562, scimark_benchmark: 947.9274,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8126, f_measure: 0.7403, kappa: 0.423, kb_relative_information_score: 316.435, mean_absolute_error: 0.2586, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7389, predictive_accuracy: 0.7435, prior_entropy: 0.9335, recall: 0.7435, relative_absolute_error: 0.5689, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4598, root_relative_squared_error: 0.9646, scimark_benchmark: 896.1742,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8156, f_measure: 0.7591, kappa: 0.4649, kb_relative_information_score: 280.0558, mean_absolute_error: 0.2878, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7578, predictive_accuracy: 0.7617, prior_entropy: 0.9335, recall: 0.7617, relative_absolute_error: 0.6332, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4185, root_relative_squared_error: 0.878, scimark_benchmark: 595.6381,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6551, f_measure: 0.6863, kappa: 0.31, kb_relative_information_score: 215.9197, mean_absolute_error: 0.3138, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.6865, predictive_accuracy: 0.6862, prior_entropy: 0.9335, recall: 0.6862, relative_absolute_error: 0.6904, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5602, root_relative_squared_error: 1.1753, scimark_benchmark: 596.7251,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7721, f_measure: 0.7522, kappa: 0.4513, kb_relative_information_score: 331.8998, mean_absolute_error: 0.2481, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7511, predictive_accuracy: 0.7539, prior_entropy: 0.9335, recall: 0.7539, relative_absolute_error: 0.546, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4854, root_relative_squared_error: 1.0184, scimark_benchmark: 918.1775,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8346, f_measure: 0.7636, kappa: 0.4726, kb_relative_information_score: 254.5861, mean_absolute_error: 0.3092, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7631, predictive_accuracy: 0.7682, prior_entropy: 0.9335, recall: 0.7682, relative_absolute_error: 0.6803, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3948, root_relative_squared_error: 0.8282, scimark_benchmark: 595.7045,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8215, f_measure: 0.7592, kappa: 0.4622, kb_relative_information_score: 257.9206, mean_absolute_error: 0.3046, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7588, predictive_accuracy: 0.7643, prior_entropy: 0.9335, recall: 0.7643, relative_absolute_error: 0.6702, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4054, root_relative_squared_error: 0.8505, scimark_benchmark: 899.082,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8282, build_cpu_time: 1.2215, build_memory: 385211087.4792, f_measure: 0.7594, kappa: 0.4645, kb_relative_information_score: 261.4701, mean_absolute_error: 0.303, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7584, predictive_accuracy: 0.763, prior_entropy: 0.9335, recall: 0.763, relative_absolute_error: 0.6666, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3984, root_relative_squared_error: 0.8359, scimark_benchmark: 946.9974,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.83, build_cpu_time: 9.204, build_memory: 231818489.8542, f_measure: 0.7645, kappa: 0.4712, kb_relative_information_score: 247.0215, mean_absolute_error: 0.3172, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7687, predictive_accuracy: 0.7734, prior_entropy: 0.9335, recall: 0.7734, relative_absolute_error: 0.6979, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3973, root_relative_squared_error: 0.8335, scimark_benchmark: 945.9579,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8281, build_cpu_time: 0.6511, build_memory: 167738287.125, f_measure: 0.7573, kappa: 0.4606, kb_relative_information_score: 262.7925, mean_absolute_error: 0.3023, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7561, predictive_accuracy: 0.7604, prior_entropy: 0.9335, recall: 0.7604, relative_absolute_error: 0.6652, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3982, root_relative_squared_error: 0.8354, scimark_benchmark: 941.7166,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8268, build_cpu_time: 4.5053, build_memory: 80881482.0938, f_measure: 0.7634, kappa: 0.4686, kb_relative_information_score: 245.7116, mean_absolute_error: 0.3178, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7672, predictive_accuracy: 0.7721, prior_entropy: 0.9335, recall: 0.7721, relative_absolute_error: 0.6993, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3983, root_relative_squared_error: 0.8356, scimark_benchmark: 921.0032,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8352, build_cpu_time: 0.4717, build_memory: 842825746.1042, f_measure: 0.7654, kappa: 0.4769, kb_relative_information_score: 253.4157, mean_absolute_error: 0.3099, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7647, predictive_accuracy: 0.7695, prior_entropy: 0.9335, recall: 0.7695, relative_absolute_error: 0.6818, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3942, root_relative_squared_error: 0.8269, scimark_benchmark: 944.9156,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8352, build_cpu_time: 0.5401, build_memory: 1866310213.2917, f_measure: 0.7654, kappa: 0.4769, kb_relative_information_score: 253.4157, mean_absolute_error: 0.3099, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7647, predictive_accuracy: 0.7695, prior_entropy: 0.9335, recall: 0.7695, relative_absolute_error: 0.6818, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3942, root_relative_squared_error: 0.8269, scimark_benchmark: 938.5838,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7509, build_cpu_time: 0.1336, build_memory: 1248303042.0625, f_measure: 0.7677, kappa: 0.4779, kb_relative_information_score: 357.7208, mean_absolute_error: 0.2341, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7735, predictive_accuracy: 0.7773, prior_entropy: 0.9335, recall: 0.7773, relative_absolute_error: 0.5151, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4549, root_relative_squared_error: 0.9543, scimark_benchmark: 936.5169,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7509, build_cpu_time: 0.1279, build_memory: 165647680.4479, f_measure: 0.7677, kappa: 0.4779, kb_relative_information_score: 357.7208, mean_absolute_error: 0.2341, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7735, predictive_accuracy: 0.7773, prior_entropy: 0.9335, recall: 0.7773, relative_absolute_error: 0.5151, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4549, root_relative_squared_error: 0.9543, scimark_benchmark: 928.8874,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.76, build_cpu_time: 0.3881, build_memory: 465745125.0208, f_measure: 0.7704, kappa: 0.484, kb_relative_information_score: 359.3672, mean_absolute_error: 0.234, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7764, predictive_accuracy: 0.7799, prior_entropy: 0.9335, recall: 0.7799, relative_absolute_error: 0.5148, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4496, root_relative_squared_error: 0.9433, scimark_benchmark: 939.7809,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8352, build_cpu_time: 16.4498, build_memory: 768868287.8125, f_measure: 0.7621, kappa: 0.4704, kb_relative_information_score: 252.7809, mean_absolute_error: 0.31, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7611, predictive_accuracy: 0.7656, prior_entropy: 0.9335, recall: 0.7656, relative_absolute_error: 0.6821, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3946, root_relative_squared_error: 0.8279, scimark_benchmark: 941.6047,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8351, build_cpu_time: 30.0292, build_memory: 1377864414.6354, f_measure: 0.7664, kappa: 0.4806, kb_relative_information_score: 252.9864, mean_absolute_error: 0.3099, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7654, predictive_accuracy: 0.7695, prior_entropy: 0.9335, recall: 0.7695, relative_absolute_error: 0.6819, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3946, root_relative_squared_error: 0.8279, scimark_benchmark: 933.8862,

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