OpenML
Supervised Classification on autoPrice

Supervised Classification on autoPrice

Task 3622 Supervised Classification autoPrice 585 runs submitted
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  • mythbusting_1 study_1 study_107 study_123 study_15 study_20 study_41 study_7 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9759, f_measure: 0.9747, kappa: 0.9434, kb_relative_information_score: 149.0231, mean_absolute_error: 0.0264, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.975, predictive_accuracy: 0.9748, prior_entropy: 0.9264, recall: 0.9748, relative_absolute_error: 0.0589, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1591, root_relative_squared_error: 0.336, scimark_benchmark: 936.6206, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9801, f_measure: 0.9811, kappa: 0.9577, kb_relative_information_score: 150.6359, mean_absolute_error: 0.0224, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9811, predictive_accuracy: 0.9811, prior_entropy: 0.9264, recall: 0.9811, relative_absolute_error: 0.0499, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1415, root_relative_squared_error: 0.2987, scimark_benchmark: 924.6116, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9815, f_measure: 0.9811, kappa: 0.9577, kb_relative_information_score: 150.5049, mean_absolute_error: 0.0229, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9811, predictive_accuracy: 0.9811, prior_entropy: 0.9264, recall: 0.9811, relative_absolute_error: 0.051, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1409, root_relative_squared_error: 0.2974, scimark_benchmark: 924.6116, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9924, f_measure: 0.9811, kappa: 0.9577, kb_relative_information_score: 149.1492, mean_absolute_error: 0.0268, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9811, predictive_accuracy: 0.9811, prior_entropy: 0.9264, recall: 0.9811, relative_absolute_error: 0.0596, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1457, root_relative_squared_error: 0.3077, scimark_benchmark: 947.9494, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9944, f_measure: 0.9748, kappa: 0.9439, kb_relative_information_score: 146.5731, mean_absolute_error: 0.0354, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9748, predictive_accuracy: 0.9748, prior_entropy: 0.9264, recall: 0.9748, relative_absolute_error: 0.0789, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1439, root_relative_squared_error: 0.3038, scimark_benchmark: 931.2336,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.466, f_measure: 0.5253, kb_relative_information_score: -0.3177, mean_absolute_error: 0.4495, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.4361, predictive_accuracy: 0.6604, prior_entropy: 0.9264, recall: 0.6604, relative_absolute_error: 1.0006, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.4738, root_relative_squared_error: 1.0005, scimark_benchmark: 938.9865,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9018, f_measure: 0.867, kappa: 0.7015, kb_relative_information_score: 111.3187, mean_absolute_error: 0.1285, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.8667, predictive_accuracy: 0.8679, prior_entropy: 0.9264, recall: 0.8679, relative_absolute_error: 0.2861, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.3287, root_relative_squared_error: 0.6941, scimark_benchmark: 943.2745, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9858, f_measure: 0.9747, kappa: 0.9434, kb_relative_information_score: 149.0274, mean_absolute_error: 0.0265, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.975, predictive_accuracy: 0.9748, prior_entropy: 0.9264, recall: 0.9748, relative_absolute_error: 0.0589, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1509, root_relative_squared_error: 0.3185, scimark_benchmark: 943.6956, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9937, f_measure: 0.9621, kappa: 0.9151, kb_relative_information_score: 146.2184, mean_absolute_error: 0.0352, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9623, predictive_accuracy: 0.9623, prior_entropy: 0.9264, recall: 0.9623, relative_absolute_error: 0.0784, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1441, root_relative_squared_error: 0.3042, scimark_benchmark: 930.32,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.466, f_measure: 0.5253, kb_relative_information_score: -0.3177, mean_absolute_error: 0.4495, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.4361, predictive_accuracy: 0.6604, prior_entropy: 0.9264, recall: 0.6604, relative_absolute_error: 1.0006, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.4738, root_relative_squared_error: 1.0005, scimark_benchmark: 932.3943,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9944, f_measure: 0.9685, kappa: 0.9296, kb_relative_information_score: 142.4272, mean_absolute_error: 0.048, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9685, predictive_accuracy: 0.9686, prior_entropy: 0.9264, recall: 0.9686, relative_absolute_error: 0.1069, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1596, root_relative_squared_error: 0.3369, scimark_benchmark: 911.0478, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5253, kb_relative_information_score: 33.1976, mean_absolute_error: 0.3396, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.4361, predictive_accuracy: 0.6604, prior_entropy: 0.9264, recall: 0.6604, relative_absolute_error: 0.7561, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.5828, root_relative_squared_error: 1.2306, scimark_benchmark: 901.0726, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9396, f_measure: 0.9438, kappa: 0.8755, kb_relative_information_score: 134.6495, mean_absolute_error: 0.0687, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9448, predictive_accuracy: 0.9434, prior_entropy: 0.9264, recall: 0.9434, relative_absolute_error: 0.153, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.2335, root_relative_squared_error: 0.493, scimark_benchmark: 904.3001,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.994, f_measure: 0.9683, kappa: 0.9289, kb_relative_information_score: 127.0852, mean_absolute_error: 0.1041, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9689, predictive_accuracy: 0.9686, prior_entropy: 0.9264, recall: 0.9686, relative_absolute_error: 0.2318, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1756, root_relative_squared_error: 0.3708, scimark_benchmark: 947.9494, usercpu_time_millis: 140, usercpu_time_millis_training: 140,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9865, f_measure: 0.9357, kappa: 0.8546, kb_relative_information_score: 118.1797, mean_absolute_error: 0.1197, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.94, predictive_accuracy: 0.9371, prior_entropy: 0.9264, recall: 0.9371, relative_absolute_error: 0.2665, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.2224, root_relative_squared_error: 0.4697, scimark_benchmark: 901.0726,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6249, f_measure: 0.6895, kappa: 0.3029, kb_relative_information_score: 63.4055, mean_absolute_error: 0.2579, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.7939, predictive_accuracy: 0.7421, prior_entropy: 0.9264, recall: 0.7421, relative_absolute_error: 0.5741, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.5078, root_relative_squared_error: 1.0722, scimark_benchmark: 891.2195, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5093, f_measure: 0.5396, kappa: 0.0243, kb_relative_information_score: 35.5213, mean_absolute_error: 0.3333, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.7785, predictive_accuracy: 0.6667, prior_entropy: 0.9264, recall: 0.6667, relative_absolute_error: 0.7421, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.5774, root_relative_squared_error: 1.2191, scimark_benchmark: 942.1229, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9713, f_measure: 0.9747, kappa: 0.9434, kb_relative_information_score: 147.1489, mean_absolute_error: 0.031, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.975, predictive_accuracy: 0.9748, prior_entropy: 0.9264, recall: 0.9748, relative_absolute_error: 0.069, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1668, root_relative_squared_error: 0.3521, scimark_benchmark: 889.9795, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9713, f_measure: 0.9747, kappa: 0.9434, kb_relative_information_score: 147.1489, mean_absolute_error: 0.031, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.975, predictive_accuracy: 0.9748, prior_entropy: 0.9264, recall: 0.9748, relative_absolute_error: 0.069, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1668, root_relative_squared_error: 0.3521, scimark_benchmark: 831.3777, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9848, f_measure: 0.9747, kappa: 0.9434, kb_relative_information_score: 149.4244, mean_absolute_error: 0.025, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.975, predictive_accuracy: 0.9748, prior_entropy: 0.9264, recall: 0.9748, relative_absolute_error: 0.0556, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1575, root_relative_squared_error: 0.3326, scimark_benchmark: 943.2817, usercpu_time_millis: 70, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4667, f_measure: 0.5036, kappa: -0.0845, kb_relative_information_score: 16.9319, mean_absolute_error: 0.3836, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.4258, predictive_accuracy: 0.6164, prior_entropy: 0.9264, recall: 0.6164, relative_absolute_error: 0.8541, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.6194, root_relative_squared_error: 1.3079, scimark_benchmark: 947.0793, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9954, f_measure: 0.9747, kappa: 0.9434, kb_relative_information_score: 144.3016, mean_absolute_error: 0.0435, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.975, predictive_accuracy: 0.9748, prior_entropy: 0.9264, recall: 0.9748, relative_absolute_error: 0.0967, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1483, root_relative_squared_error: 0.3132, scimark_benchmark: 945.6434, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9924, f_measure: 0.9619, kappa: 0.9143, kb_relative_information_score: 144.8913, mean_absolute_error: 0.0373, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9629, predictive_accuracy: 0.9623, prior_entropy: 0.9264, recall: 0.9623, relative_absolute_error: 0.0831, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1748, root_relative_squared_error: 0.3692, scimark_benchmark: 923.9763, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5093, f_measure: 0.5396, kappa: 0.0243, kb_relative_information_score: 35.5213, mean_absolute_error: 0.3333, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.7785, predictive_accuracy: 0.6667, prior_entropy: 0.9264, recall: 0.6667, relative_absolute_error: 0.7421, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.5774, root_relative_squared_error: 1.2191, scimark_benchmark: 928.3108, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9537, f_measure: 0.9682, kappa: 0.9283, kb_relative_information_score: 147.0579, mean_absolute_error: 0.0314, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.97, predictive_accuracy: 0.9686, prior_entropy: 0.9264, recall: 0.9686, relative_absolute_error: 0.07, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1773, root_relative_squared_error: 0.3744, scimark_benchmark: 939.0833, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9835, build_cpu_time: 0.4408, build_memory: 1067752097.1069, f_measure: 0.9435, kappa: 0.8744, kb_relative_information_score: 137.3548, mean_absolute_error: 0.0583, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9437, predictive_accuracy: 0.9434, prior_entropy: 0.9264, recall: 0.9434, relative_absolute_error: 0.1298, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.2268, root_relative_squared_error: 0.479, scimark_benchmark: 940.2036,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9825, build_cpu_time: 0.1848, build_memory: 754852002.3648, f_measure: 0.9435, kappa: 0.8744, kb_relative_information_score: 137.6075, mean_absolute_error: 0.0574, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9437, predictive_accuracy: 0.9434, prior_entropy: 0.9264, recall: 0.9434, relative_absolute_error: 0.1279, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.2259, root_relative_squared_error: 0.4771, scimark_benchmark: 916.3022,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9832, build_cpu_time: 0.1013, build_memory: 1082473704.1509, f_measure: 0.9435, kappa: 0.8744, kb_relative_information_score: 136.6389, mean_absolute_error: 0.06, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9437, predictive_accuracy: 0.9434, prior_entropy: 0.9264, recall: 0.9434, relative_absolute_error: 0.1336, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.227, root_relative_squared_error: 0.4794, scimark_benchmark: 927.1482,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9755, build_cpu_time: 0.0506, build_memory: 1182947646.1384, f_measure: 0.9433, kappa: 0.8732, kb_relative_information_score: 135.4958, mean_absolute_error: 0.0631, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9432, predictive_accuracy: 0.9434, prior_entropy: 0.9264, recall: 0.9434, relative_absolute_error: 0.1406, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.2323, root_relative_squared_error: 0.4906, scimark_benchmark: 941.7891,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9961, build_cpu_time: 0.0075, build_memory: 577218716.8805, f_measure: 0.9811, kappa: 0.9577, kb_relative_information_score: 150.5108, mean_absolute_error: 0.0226, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9811, predictive_accuracy: 0.9811, prior_entropy: 0.9264, recall: 0.9811, relative_absolute_error: 0.0504, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1401, root_relative_squared_error: 0.2959, scimark_benchmark: 935.8685,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9925, build_cpu_time: 0.0113, build_memory: 359534227.6226, f_measure: 0.9621, kappa: 0.9151, kb_relative_information_score: 145.5863, mean_absolute_error: 0.0355, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9623, predictive_accuracy: 0.9623, prior_entropy: 0.9264, recall: 0.9623, relative_absolute_error: 0.079, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.181, root_relative_squared_error: 0.3823, scimark_benchmark: 940.159,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9925, build_cpu_time: 0.0248, build_memory: 1257936235.7233, f_measure: 0.9621, kappa: 0.9151, kb_relative_information_score: 145.1077, mean_absolute_error: 0.0365, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9623, predictive_accuracy: 0.9623, prior_entropy: 0.9264, recall: 0.9623, relative_absolute_error: 0.0812, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1847, root_relative_squared_error: 0.39, scimark_benchmark: 932.9956,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9925, build_cpu_time: 0.0162, build_memory: 76826690.8679, f_measure: 0.9621, kappa: 0.9151, kb_relative_information_score: 145.1077, mean_absolute_error: 0.0365, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9623, predictive_accuracy: 0.9623, prior_entropy: 0.9264, recall: 0.9623, relative_absolute_error: 0.0812, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1847, root_relative_squared_error: 0.39, scimark_benchmark: 940.159,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9925, build_cpu_time: 0.0198, build_memory: 1067501830.1384, f_measure: 0.9621, kappa: 0.9151, kb_relative_information_score: 145.1077, mean_absolute_error: 0.0365, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9623, predictive_accuracy: 0.9623, prior_entropy: 0.9264, recall: 0.9623, relative_absolute_error: 0.0812, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1847, root_relative_squared_error: 0.39, scimark_benchmark: 932.9956,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9579, build_cpu_time: 0.0041, build_memory: 394106962.9182, f_measure: 0.9623, kappa: 0.9159, kb_relative_information_score: 144.7342, mean_absolute_error: 0.0377, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9623, predictive_accuracy: 0.9623, prior_entropy: 0.9264, recall: 0.9623, relative_absolute_error: 0.084, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1943, root_relative_squared_error: 0.4102, scimark_benchmark: 907.1899,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9579, build_cpu_time: 0.0044, build_memory: 89776424.3522, f_measure: 0.9623, kappa: 0.9159, kb_relative_information_score: 144.7342, mean_absolute_error: 0.0377, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9623, predictive_accuracy: 0.9623, prior_entropy: 0.9264, recall: 0.9623, relative_absolute_error: 0.084, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1943, root_relative_squared_error: 0.4102, scimark_benchmark: 877.9084,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9579, build_cpu_time: 0.0021, build_memory: 1543143912.2013, f_measure: 0.9623, kappa: 0.9159, kb_relative_information_score: 144.7342, mean_absolute_error: 0.0377, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9623, predictive_accuracy: 0.9623, prior_entropy: 0.9264, recall: 0.9623, relative_absolute_error: 0.084, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1943, root_relative_squared_error: 0.4102, scimark_benchmark: 934.6076,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5093, build_cpu_time: 0.0128, build_memory: 284137095.6478, f_measure: 0.5396, kappa: 0.0243, kb_relative_information_score: 35.5213, mean_absolute_error: 0.3333, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.7785, predictive_accuracy: 0.6667, prior_entropy: 0.9264, recall: 0.6667, relative_absolute_error: 0.7421, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.5774, root_relative_squared_error: 1.2191, scimark_benchmark: 936.7073,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9901, build_cpu_time: 0.0008, build_memory: 242401697.8113, f_measure: 0.9499, kappa: 0.8888, kb_relative_information_score: 137.2262, mean_absolute_error: 0.0587, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9504, predictive_accuracy: 0.9497, prior_entropy: 0.9264, recall: 0.9497, relative_absolute_error: 0.1308, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.221, root_relative_squared_error: 0.4666, scimark_benchmark: 945.7844,

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