Task
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: 0.9954, build_cpu_time: 0.009, build_memory: 29245714.4654, 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: 935.2997,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9604, build_cpu_time: 0.0092, build_memory: 1823544570.566, f_measure: 0.9623, kappa: 0.9159, kb_relative_information_score: 143.8779, mean_absolute_error: 0.0406, 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: 0.0903, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1967, root_relative_squared_error: 0.4153, scimark_benchmark: 909.5718,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9979, build_cpu_time: 0.0324, build_memory: 990530901.5346, f_measure: 0.9747, kappa: 0.9434, kb_relative_information_score: 142.9804, mean_absolute_error: 0.0487, 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: 0.1084, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1415, root_relative_squared_error: 0.2988, scimark_benchmark: 892.8005,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9979, build_cpu_time: 0.0365, build_memory: 741607184.1509, f_measure: 0.9747, kappa: 0.9434, kb_relative_information_score: 142.9804, mean_absolute_error: 0.0487, 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: 0.1084, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1415, root_relative_squared_error: 0.2988, scimark_benchmark: 943.7751,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9753, build_cpu_time: 0.1021, build_memory: 1419649242.4151, f_measure: 0.9563, kappa: 0.9032, kb_relative_information_score: 142.6756, mean_absolute_error: 0.0431, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9573, predictive_accuracy: 0.956, prior_entropy: 0.9264, recall: 0.956, relative_absolute_error: 0.0959, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.2046, root_relative_squared_error: 0.4321, scimark_benchmark: 943.5504,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9753, build_cpu_time: 0.0694, build_memory: 1000269940.478, f_measure: 0.9563, kappa: 0.9032, kb_relative_information_score: 142.6756, mean_absolute_error: 0.0431, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9573, predictive_accuracy: 0.956, prior_entropy: 0.9264, recall: 0.956, relative_absolute_error: 0.0959, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.2046, root_relative_squared_error: 0.4321, scimark_benchmark: 908.8705,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9753, build_cpu_time: 0.0752, build_memory: 1496894818.9182, f_measure: 0.9563, kappa: 0.9032, kb_relative_information_score: 142.6753, mean_absolute_error: 0.0431, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9573, predictive_accuracy: 0.956, prior_entropy: 0.9264, recall: 0.956, relative_absolute_error: 0.0959, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.2046, root_relative_squared_error: 0.4321, scimark_benchmark: 943.2074,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9821, build_cpu_time: 0.0631, build_memory: 1000211932.5786, f_measure: 0.9563, kappa: 0.9032, kb_relative_information_score: 142.0277, mean_absolute_error: 0.0453, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9573, predictive_accuracy: 0.956, prior_entropy: 0.9264, recall: 0.956, relative_absolute_error: 0.1009, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.2082, root_relative_squared_error: 0.4396, scimark_benchmark: 943.2074,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9786, build_cpu_time: 0.0046, build_memory: 834970092.0755, f_measure: 0.9623, kappa: 0.9159, kb_relative_information_score: 144.3975, mean_absolute_error: 0.039, 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: 0.0867, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1948, root_relative_squared_error: 0.4113, scimark_benchmark: 943.5504,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9809, build_cpu_time: 0.024, build_memory: 949692384.2516, f_measure: 0.9499, kappa: 0.8888, kb_relative_information_score: 140.1126, mean_absolute_error: 0.0502, 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: 0.1118, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.2215, root_relative_squared_error: 0.4678, scimark_benchmark: 943.2074,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9478, build_cpu_time: 0.0289, build_memory: 363886379.6226, f_measure: 0.9497, kappa: 0.8878, kb_relative_information_score: 140.1625, mean_absolute_error: 0.0501, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9497, predictive_accuracy: 0.9497, prior_entropy: 0.9264, recall: 0.9497, relative_absolute_error: 0.1114, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.2198, root_relative_squared_error: 0.4641, scimark_benchmark: 916.8903,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9479, build_cpu_time: 0.0348, build_memory: 1456645203.522, f_measure: 0.9497, kappa: 0.8878, kb_relative_information_score: 139.5832, mean_absolute_error: 0.052, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9497, predictive_accuracy: 0.9497, prior_entropy: 0.9264, recall: 0.9497, relative_absolute_error: 0.1158, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.2251, root_relative_squared_error: 0.4754, scimark_benchmark: 939.0159,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9479, build_cpu_time: 0.0737, build_memory: 556471950.8931, f_measure: 0.9433, kappa: 0.8732, kb_relative_information_score: 137.7633, mean_absolute_error: 0.0566, 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: 0.126, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.2379, root_relative_squared_error: 0.5024, scimark_benchmark: 927.3354,
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: 0.5093, 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: 0.6249, 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: 0.994, 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: 0.9396, 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: 0.9537, 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: 0.5093, 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: 0.9848, 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: 0.9713, 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: 0.9944, 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: 0.9937, 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: 0.9858, 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: 0.9835, 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: 0.9924, 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: 0.9954, 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: 0.4667, 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: 0.5, 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: 0.466, 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: 0.9865, 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: 0.9954, build_cpu_time: 0.0077, build_memory: 839363905.0566, 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: 920.6195,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9954, build_cpu_time: 0.0093, build_memory: 350101410.4654, 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: 938.0657,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9954, build_cpu_time: 0.0202, build_memory: 1866635914.1132, 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: 941.9633,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9921, build_cpu_time: 1.7468, build_memory: 1353269149.9371, f_measure: 0.9621, kappa: 0.9151, kb_relative_information_score: 135.039, mean_absolute_error: 0.0725, 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: 0.1615, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1721, root_relative_squared_error: 0.3634, scimark_benchmark: 944.9147,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9919, build_cpu_time: 3.5826, build_memory: 3465796085.2327, f_measure: 0.9621, kappa: 0.9151, kb_relative_information_score: 134.4208, mean_absolute_error: 0.0748, 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: 0.1666, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.173, root_relative_squared_error: 0.3652, scimark_benchmark: 945.8425,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9695, build_cpu_time: 0.0491, build_memory: 241993219.522, f_measure: 0.9486, kappa: 0.8836, kb_relative_information_score: 139.8033, mean_absolute_error: 0.0535, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.9532, predictive_accuracy: 0.9497, prior_entropy: 0.9264, recall: 0.9497, relative_absolute_error: 0.119, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1915, root_relative_squared_error: 0.4043, scimark_benchmark: 933.4123,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9687, build_cpu_time: 0.1227, build_memory: 493502761.6101, f_measure: 0.9621, kappa: 0.9151, kb_relative_information_score: 140.4087, mean_absolute_error: 0.0528, 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: 0.1176, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1798, root_relative_squared_error: 0.3797, scimark_benchmark: 946.0329,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4378, build_cpu_time: 0.0284, build_memory: 387600484.2264, f_measure: 0.489, kappa: -0.15, kb_relative_information_score: 0.6661, mean_absolute_error: 0.4277, mean_prior_absolute_error: 0.4492, number_of_instances: 159, precision: 0.4368, predictive_accuracy: 0.5723, prior_entropy: 0.9264, recall: 0.5723, relative_absolute_error: 0.9521, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.654, root_relative_squared_error: 1.3809, scimark_benchmark: 933.1047,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.997, build_cpu_time: 0.0306, build_memory: 3263086270.0377, f_measure: 0.9683, kappa: 0.9289, kb_relative_information_score: 141.6359, mean_absolute_error: 0.0511, 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: 0.1138, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1499, root_relative_squared_error: 0.3165, scimark_benchmark: 941.3608,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9961, build_cpu_time: 0.0076, build_memory: 2793921610.4151, f_measure: 0.9683, kappa: 0.9289, kb_relative_information_score: 140.852, mean_absolute_error: 0.0531, 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: 0.1183, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1584, root_relative_squared_error: 0.3344, scimark_benchmark: 949.2096,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9961, build_cpu_time: 0.0077, build_memory: 2856500694.4403, f_measure: 0.9683, kappa: 0.9289, kb_relative_information_score: 140.852, mean_absolute_error: 0.0531, 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: 0.1183, root_mean_prior_squared_error: 0.4736, root_mean_squared_error: 0.1584, root_relative_squared_error: 0.3344, scimark_benchmark: 941.5201,

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