OpenML
Supervised Classification on lung-cancer

Supervised Classification on lung-cancer

Task 2372 Supervised Classification lung-cancer 458 runs submitted
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  • mythbusting_1 study_1 study_107 study_123 study_15 study_20 study_41 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.2347, kb_relative_information_score: 4.6963, mean_absolute_error: 0.3958, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.165, predictive_accuracy: 0.4063, prior_entropy: 1.57, recall: 0.4063, relative_absolute_error: 0.9011, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.6292, root_relative_squared_error: 1.3431, scimark_benchmark: 1340.5125, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6775, f_measure: 0.5568, kappa: 0.3431, kb_relative_information_score: 11.3692, mean_absolute_error: 0.3192, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.5568, predictive_accuracy: 0.5625, prior_entropy: 1.57, recall: 0.5625, relative_absolute_error: 0.7267, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.523, root_relative_squared_error: 1.1165, scimark_benchmark: 1325.3966,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6775, f_measure: 0.5568, kappa: 0.3431, kb_relative_information_score: 11.3692, mean_absolute_error: 0.3192, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.5568, predictive_accuracy: 0.5625, prior_entropy: 1.57, recall: 0.5625, relative_absolute_error: 0.7267, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.523, root_relative_squared_error: 1.1165, scimark_benchmark: 1328.1785, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.626, f_measure: 0.4399, kappa: 0.1416, kb_relative_information_score: 4.942, mean_absolute_error: 0.4047, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.4437, predictive_accuracy: 0.4375, prior_entropy: 1.57, recall: 0.4375, relative_absolute_error: 0.9212, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.4596, root_relative_squared_error: 0.9811, scimark_benchmark: 1342.4614, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6775, f_measure: 0.5568, kappa: 0.3431, kb_relative_information_score: 11.3692, mean_absolute_error: 0.3192, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.5568, predictive_accuracy: 0.5625, prior_entropy: 1.57, recall: 0.5625, relative_absolute_error: 0.7267, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.523, root_relative_squared_error: 1.1165, scimark_benchmark: 1342.6744,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.699, f_measure: 0.5688, kappa: 0.3383, kb_relative_information_score: 11.0327, mean_absolute_error: 0.3213, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.596, predictive_accuracy: 0.5625, prior_entropy: 1.57, recall: 0.5625, relative_absolute_error: 0.7315, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.5132, root_relative_squared_error: 1.0956, scimark_benchmark: 1321.4561, usercpu_time_millis: 290, usercpu_time_millis_training: 290,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7173, f_measure: 0.5966, kappa: 0.3678, kb_relative_information_score: 6.8098, mean_absolute_error: 0.3815, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.6393, predictive_accuracy: 0.5938, prior_entropy: 1.57, recall: 0.5938, relative_absolute_error: 0.8685, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.4279, root_relative_squared_error: 0.9136, scimark_benchmark: 1371.174,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5626, f_measure: 0.4359, kappa: 0.1441, kb_relative_information_score: 7.197, mean_absolute_error: 0.375, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.4361, predictive_accuracy: 0.4375, prior_entropy: 1.57, recall: 0.4375, relative_absolute_error: 0.8537, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.6124, root_relative_squared_error: 1.3073, scimark_benchmark: 1345.0202,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.2347, kb_relative_information_score: 4.6963, mean_absolute_error: 0.3958, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.165, predictive_accuracy: 0.4063, prior_entropy: 1.57, recall: 0.4063, relative_absolute_error: 0.9011, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.6292, root_relative_squared_error: 1.3431, scimark_benchmark: 1348.2804, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6775, f_measure: 0.5568, kappa: 0.3431, kb_relative_information_score: 11.3692, mean_absolute_error: 0.3192, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.5568, predictive_accuracy: 0.5625, prior_entropy: 1.57, recall: 0.5625, relative_absolute_error: 0.7267, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.523, root_relative_squared_error: 1.1165, scimark_benchmark: 1286.0816,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.699, f_measure: 0.5688, kappa: 0.3383, kb_relative_information_score: 11.0327, mean_absolute_error: 0.3213, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.596, predictive_accuracy: 0.5625, prior_entropy: 1.57, recall: 0.5625, relative_absolute_error: 0.7315, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.5132, root_relative_squared_error: 1.0956, scimark_benchmark: 1274.7011, usercpu_time_millis: 300, usercpu_time_millis_training: 300,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7173, f_measure: 0.5966, kappa: 0.3678, kb_relative_information_score: 6.8098, mean_absolute_error: 0.3815, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.6393, predictive_accuracy: 0.5938, prior_entropy: 1.57, recall: 0.5938, relative_absolute_error: 0.8685, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.4279, root_relative_squared_error: 0.9136, scimark_benchmark: 1344.0499, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.2347, kb_relative_information_score: 4.6963, mean_absolute_error: 0.3958, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.165, predictive_accuracy: 0.4063, prior_entropy: 1.57, recall: 0.4063, relative_absolute_error: 0.9011, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.6292, root_relative_squared_error: 1.3431, scimark_benchmark: 1314.0283, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6863, f_measure: 0.5369, kappa: 0.2857, kb_relative_information_score: 10.3473, mean_absolute_error: 0.3294, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.5491, predictive_accuracy: 0.5313, prior_entropy: 1.57, recall: 0.5313, relative_absolute_error: 0.7498, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.5357, root_relative_squared_error: 1.1436, scimark_benchmark: 1260.1387,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6775, f_measure: 0.5568, kappa: 0.3431, kb_relative_information_score: 11.3692, mean_absolute_error: 0.3192, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.5568, predictive_accuracy: 0.5625, prior_entropy: 1.57, recall: 0.5625, relative_absolute_error: 0.7267, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.523, root_relative_squared_error: 1.1165, scimark_benchmark: 1354.3488,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6775, f_measure: 0.5568, kappa: 0.3431, kb_relative_information_score: 11.3692, mean_absolute_error: 0.3192, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.5568, predictive_accuracy: 0.5625, prior_entropy: 1.57, recall: 0.5625, relative_absolute_error: 0.7267, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.523, root_relative_squared_error: 1.1165, scimark_benchmark: 1354.3488,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7173, f_measure: 0.5966, kappa: 0.3678, kb_relative_information_score: 6.8098, mean_absolute_error: 0.3815, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.6393, predictive_accuracy: 0.5938, prior_entropy: 1.57, recall: 0.5938, relative_absolute_error: 0.8685, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.4279, root_relative_squared_error: 0.9136, scimark_benchmark: 1260.1387, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6863, f_measure: 0.5369, kappa: 0.2857, kb_relative_information_score: 10.3473, mean_absolute_error: 0.3294, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.5491, predictive_accuracy: 0.5313, prior_entropy: 1.57, recall: 0.5313, relative_absolute_error: 0.7498, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.5357, root_relative_squared_error: 1.1436, scimark_benchmark: 938.0414,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6863, f_measure: 0.5369, kappa: 0.2857, kb_relative_information_score: 10.3473, mean_absolute_error: 0.3294, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.5491, predictive_accuracy: 0.5313, prior_entropy: 1.57, recall: 0.5313, relative_absolute_error: 0.7498, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.5357, root_relative_squared_error: 1.1436, scimark_benchmark: 932.5646,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6135, f_measure: 0.4692, kappa: 0.1868, kb_relative_information_score: 7.4146, mean_absolute_error: 0.3737, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.4817, predictive_accuracy: 0.4688, prior_entropy: 1.57, recall: 0.4688, relative_absolute_error: 0.8507, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.5626, root_relative_squared_error: 1.2011, scimark_benchmark: 1330.9699, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5523, f_measure: 0.4105, kappa: 0.1019, kb_relative_information_score: 4.943, mean_absolute_error: 0.4082, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.4286, predictive_accuracy: 0.4063, prior_entropy: 1.57, recall: 0.4063, relative_absolute_error: 0.9291, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.5759, root_relative_squared_error: 1.2295, scimark_benchmark: 1345.7204,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5849, f_measure: 0.3939, kappa: 0.1098, kb_relative_information_score: 4.6803, mean_absolute_error: 0.4063, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.3903, predictive_accuracy: 0.4063, prior_entropy: 1.57, recall: 0.4063, relative_absolute_error: 0.9248, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.4564, root_relative_squared_error: 0.9744, scimark_benchmark: 869.6028, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.656, f_measure: 0.5601, kappa: 0.3392, kb_relative_information_score: 10.8938, mean_absolute_error: 0.328, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.5594, predictive_accuracy: 0.5625, prior_entropy: 1.57, recall: 0.5625, relative_absolute_error: 0.7466, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.497, root_relative_squared_error: 1.0609, scimark_benchmark: 869.6028, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5968, f_measure: 0.4148, kappa: 0.1652, kb_relative_information_score: 3.8249, mean_absolute_error: 0.4148, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.4119, predictive_accuracy: 0.4375, prior_entropy: 1.57, recall: 0.4375, relative_absolute_error: 0.9443, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.4594, root_relative_squared_error: 0.9808, scimark_benchmark: 915.9693, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5968, f_measure: 0.4148, kappa: 0.1652, kb_relative_information_score: 3.8249, mean_absolute_error: 0.4148, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.4119, predictive_accuracy: 0.4375, prior_entropy: 1.57, recall: 0.4375, relative_absolute_error: 0.9443, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.4594, root_relative_squared_error: 0.9808, scimark_benchmark: 939.5205,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5968, f_measure: 0.4148, kappa: 0.1652, kb_relative_information_score: 3.8249, mean_absolute_error: 0.4148, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.4119, predictive_accuracy: 0.4375, prior_entropy: 1.57, recall: 0.4375, relative_absolute_error: 0.9443, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.4594, root_relative_squared_error: 0.9808, scimark_benchmark: 1372.2145,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5968, f_measure: 0.4148, kappa: 0.1652, kb_relative_information_score: 3.8249, mean_absolute_error: 0.4148, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.4119, predictive_accuracy: 0.4375, prior_entropy: 1.57, recall: 0.4375, relative_absolute_error: 0.9443, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.4594, root_relative_squared_error: 0.9808, scimark_benchmark: 1304.9611,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5976, f_measure: 0.4148, kappa: 0.1652, kb_relative_information_score: 3.8736, mean_absolute_error: 0.4146, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.4119, predictive_accuracy: 0.4375, prior_entropy: 1.57, recall: 0.4375, relative_absolute_error: 0.9438, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.4571, root_relative_squared_error: 0.9758, scimark_benchmark: 933.3136,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6421, f_measure: 0.4794, kappa: 0.2127, kb_relative_information_score: 6.053, mean_absolute_error: 0.3881, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.5743, predictive_accuracy: 0.4688, prior_entropy: 1.57, recall: 0.4688, relative_absolute_error: 0.8835, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.4632, root_relative_squared_error: 0.9888, scimark_benchmark: 1304.6687,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6928, f_measure: 0.4766, kappa: 0.2727, kb_relative_information_score: 8.4891, mean_absolute_error: 0.3614, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.5521, predictive_accuracy: 0.5, prior_entropy: 1.57, recall: 0.5, relative_absolute_error: 0.8226, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.467, root_relative_squared_error: 0.9969, scimark_benchmark: 1335.643,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6829, f_measure: 0.2969, kappa: 0.0573, kb_relative_information_score: 7.7033, mean_absolute_error: 0.3611, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.4829, predictive_accuracy: 0.4375, prior_entropy: 1.57, recall: 0.4375, relative_absolute_error: 0.822, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.4615, root_relative_squared_error: 0.9852, scimark_benchmark: 916.5769, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5902, f_measure: 0.375, kappa: 0.0504, kb_relative_information_score: 6.7922, mean_absolute_error: 0.3819, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.375, predictive_accuracy: 0.375, prior_entropy: 1.57, recall: 0.375, relative_absolute_error: 0.8695, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.4811, root_relative_squared_error: 1.0271, scimark_benchmark: 916.5955, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5899, f_measure: 0.464, kappa: 0.1965, kb_relative_information_score: 6.4546, mean_absolute_error: 0.3877, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.4754, predictive_accuracy: 0.4688, prior_entropy: 1.57, recall: 0.4688, relative_absolute_error: 0.8826, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.5159, root_relative_squared_error: 1.1013, scimark_benchmark: 895.5332, usercpu_time_millis: 70, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5626, f_measure: 0.4359, kappa: 0.1441, kb_relative_information_score: 7.197, mean_absolute_error: 0.375, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.4361, predictive_accuracy: 0.4375, prior_entropy: 1.57, recall: 0.4375, relative_absolute_error: 0.8537, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.6124, root_relative_squared_error: 1.3073, scimark_benchmark: 939.449,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.699, f_measure: 0.5688, kappa: 0.3383, kb_relative_information_score: 11.0327, mean_absolute_error: 0.3213, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.596, predictive_accuracy: 0.5625, prior_entropy: 1.57, recall: 0.5625, relative_absolute_error: 0.7315, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.5132, root_relative_squared_error: 1.0956, scimark_benchmark: 1304.9611, usercpu_time_millis: 310, usercpu_time_millis_training: 310,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7173, f_measure: 0.5966, kappa: 0.3678, kb_relative_information_score: 6.8098, mean_absolute_error: 0.3815, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.6393, predictive_accuracy: 0.5938, prior_entropy: 1.57, recall: 0.5938, relative_absolute_error: 0.8685, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.4279, root_relative_squared_error: 0.9136, scimark_benchmark: 1346.9602, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5182, f_measure: 0.3104, kappa: 0.0317, kb_relative_information_score: 4.1363, mean_absolute_error: 0.4271, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.2963, predictive_accuracy: 0.3438, prior_entropy: 1.57, recall: 0.3438, relative_absolute_error: 0.9722, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.6455, root_relative_squared_error: 1.3781, scimark_benchmark: 1301.9956,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6175, f_measure: 0.4356, kappa: 0.1553, kb_relative_information_score: 6.1167, mean_absolute_error: 0.3847, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.4632, predictive_accuracy: 0.4688, prior_entropy: 1.57, recall: 0.4688, relative_absolute_error: 0.8758, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.4534, root_relative_squared_error: 0.968, scimark_benchmark: 1319.9043,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6205, f_measure: 0.5193, kappa: 0.276, kb_relative_information_score: 7.7935, mean_absolute_error: 0.3666, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.5474, predictive_accuracy: 0.5313, prior_entropy: 1.57, recall: 0.5313, relative_absolute_error: 0.8345, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.4819, root_relative_squared_error: 1.0287, scimark_benchmark: 1304.6687, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5301, f_measure: 0.4031, kappa: 0.0732, kb_relative_information_score: 5.4387, mean_absolute_error: 0.3958, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.4167, predictive_accuracy: 0.4063, prior_entropy: 1.57, recall: 0.4063, relative_absolute_error: 0.9011, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.6292, root_relative_squared_error: 1.3431, scimark_benchmark: 1291.6995,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.1235, kb_relative_information_score: 0.7914, mean_absolute_error: 0.4792, mean_prior_absolute_error: 0.4393, number_of_instances: 32, precision: 0.0791, predictive_accuracy: 0.2813, prior_entropy: 1.57, recall: 0.2813, relative_absolute_error: 1.0908, root_mean_prior_squared_error: 0.4684, root_mean_squared_error: 0.6922, root_relative_squared_error: 1.4778, scimark_benchmark: 1368.9272,

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