OpenML
Supervised Classification on squash-unstored

Supervised Classification on squash-unstored

Task 3061 Supervised Classification squash-unstored 306 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7188, f_measure: 0.5745, kappa: 0.3239, kb_relative_information_score: 7.1259, mean_absolute_error: 0.2861, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.6415, predictive_accuracy: 0.5882, prior_entropy: 1.3486, recall: 0.5882, relative_absolute_error: 0.7041, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.4839, root_relative_squared_error: 1.0471, scimark_benchmark: 933.1165,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7188, f_measure: 0.5745, kappa: 0.3239, kb_relative_information_score: 7.1259, mean_absolute_error: 0.2861, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.6415, predictive_accuracy: 0.5882, prior_entropy: 1.3486, recall: 0.5882, relative_absolute_error: 0.7041, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.4839, root_relative_squared_error: 1.0471, scimark_benchmark: 933.1165,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7188, f_measure: 0.5745, kappa: 0.3239, kb_relative_information_score: 7.1259, mean_absolute_error: 0.2861, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.6415, predictive_accuracy: 0.5882, prior_entropy: 1.3486, recall: 0.5882, relative_absolute_error: 0.7041, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.4839, root_relative_squared_error: 1.0471, scimark_benchmark: 926.6704,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.1841, kb_relative_information_score: -0.4325, mean_absolute_error: 0.4314, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.1246, predictive_accuracy: 0.3529, prior_entropy: 1.3486, recall: 0.3529, relative_absolute_error: 1.0614, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.6568, root_relative_squared_error: 1.4212, scimark_benchmark: 1350.073,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7188, f_measure: 0.5745, kappa: 0.3239, kb_relative_information_score: 7.1259, mean_absolute_error: 0.2861, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.6415, predictive_accuracy: 0.5882, prior_entropy: 1.3486, recall: 0.5882, relative_absolute_error: 0.7041, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.4839, root_relative_squared_error: 1.0471, scimark_benchmark: 1322.7383,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7254, f_measure: 0.5289, kappa: 0.2959, kb_relative_information_score: 7.3475, mean_absolute_error: 0.2875, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.482, predictive_accuracy: 0.5882, prior_entropy: 1.3486, recall: 0.5882, relative_absolute_error: 0.7073, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.4739, root_relative_squared_error: 1.0253, scimark_benchmark: 1343.2125,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.63, f_measure: 0.4786, kappa: 0.1856, kb_relative_information_score: 3.8956, mean_absolute_error: 0.319, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.437, predictive_accuracy: 0.5294, prior_entropy: 1.3486, recall: 0.5294, relative_absolute_error: 0.7848, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.5427, root_relative_squared_error: 1.1744, scimark_benchmark: 1345.7204,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.63, f_measure: 0.4786, kappa: 0.1856, kb_relative_information_score: 3.8956, mean_absolute_error: 0.319, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.437, predictive_accuracy: 0.5294, prior_entropy: 1.3486, recall: 0.5294, relative_absolute_error: 0.7848, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.5427, root_relative_squared_error: 1.1744, scimark_benchmark: 1355.2525,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7603, f_measure: 0.6373, kappa: 0.4, kb_relative_information_score: 7.714, mean_absolute_error: 0.2493, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.6941, predictive_accuracy: 0.6471, prior_entropy: 1.3486, recall: 0.6471, relative_absolute_error: 0.6135, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.4891, root_relative_squared_error: 1.0583, scimark_benchmark: 1337.6765, usercpu_time_millis: 70, usercpu_time_millis_testing: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.686, f_measure: 0.5325, kappa: 0.2788, kb_relative_information_score: 5.5347, mean_absolute_error: 0.2745, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.492, predictive_accuracy: 0.5882, prior_entropy: 1.3486, recall: 0.5882, relative_absolute_error: 0.6755, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.5236, root_relative_squared_error: 1.133, scimark_benchmark: 1320.9026, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.686, f_measure: 0.5325, kappa: 0.2788, kb_relative_information_score: 5.5347, mean_absolute_error: 0.2745, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.492, predictive_accuracy: 0.5882, prior_entropy: 1.3486, recall: 0.5882, relative_absolute_error: 0.6755, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.5236, root_relative_squared_error: 1.133, scimark_benchmark: 1320.9026, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7148, f_measure: 0.4786, kappa: 0.1856, kb_relative_information_score: 2.6899, mean_absolute_error: 0.3541, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.437, predictive_accuracy: 0.5294, prior_entropy: 1.3486, recall: 0.5294, relative_absolute_error: 0.8713, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.455, root_relative_squared_error: 0.9846, scimark_benchmark: 1311.9814, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7213, f_measure: 0.4786, kappa: 0.1856, kb_relative_information_score: 2.8113, mean_absolute_error: 0.3511, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.437, predictive_accuracy: 0.5294, prior_entropy: 1.3486, recall: 0.5294, relative_absolute_error: 0.8639, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.4553, root_relative_squared_error: 0.9852, scimark_benchmark: 1342.2985, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7124, f_measure: 0.4786, kappa: 0.1856, kb_relative_information_score: 2.9378, mean_absolute_error: 0.3477, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.437, predictive_accuracy: 0.5294, prior_entropy: 1.3486, recall: 0.5294, relative_absolute_error: 0.8555, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.4589, root_relative_squared_error: 0.9931, scimark_benchmark: 1347.5461, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.63, f_measure: 0.4786, kappa: 0.1856, kb_relative_information_score: 3.8956, mean_absolute_error: 0.319, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.437, predictive_accuracy: 0.5294, prior_entropy: 1.3486, recall: 0.5294, relative_absolute_error: 0.7848, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.5427, root_relative_squared_error: 1.1744, scimark_benchmark: 922.1419,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.63, f_measure: 0.4786, kappa: 0.1856, kb_relative_information_score: 3.8956, mean_absolute_error: 0.319, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.437, predictive_accuracy: 0.5294, prior_entropy: 1.3486, recall: 0.5294, relative_absolute_error: 0.7848, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.5427, root_relative_squared_error: 1.1744, scimark_benchmark: 916.5769, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6743, f_measure: 0.5325, kappa: 0.2788, kb_relative_information_score: 3.4787, mean_absolute_error: 0.3336, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.492, predictive_accuracy: 0.5882, prior_entropy: 1.3486, recall: 0.5882, relative_absolute_error: 0.8207, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.4571, root_relative_squared_error: 0.989, scimark_benchmark: 906.4475, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.63, f_measure: 0.4786, kappa: 0.1856, kb_relative_information_score: 3.8956, mean_absolute_error: 0.319, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.437, predictive_accuracy: 0.5294, prior_entropy: 1.3486, recall: 0.5294, relative_absolute_error: 0.7848, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.5427, root_relative_squared_error: 1.1744, scimark_benchmark: 1314.9535,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.1841, kb_relative_information_score: -0.4325, mean_absolute_error: 0.4314, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.1246, predictive_accuracy: 0.3529, prior_entropy: 1.3486, recall: 0.3529, relative_absolute_error: 1.0614, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.6568, root_relative_squared_error: 1.4212, scimark_benchmark: 1334.6745,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7039, f_measure: 0.5745, kappa: 0.3239, kb_relative_information_score: 6.9971, mean_absolute_error: 0.2892, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.6415, predictive_accuracy: 0.5882, prior_entropy: 1.3486, recall: 0.5882, relative_absolute_error: 0.7115, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.4858, root_relative_squared_error: 1.0512, scimark_benchmark: 937.1527, usercpu_time_millis: 40, usercpu_time_millis_testing: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.63, f_measure: 0.4786, kappa: 0.1856, kb_relative_information_score: 3.8956, mean_absolute_error: 0.319, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.437, predictive_accuracy: 0.5294, prior_entropy: 1.3486, recall: 0.5294, relative_absolute_error: 0.7848, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.5427, root_relative_squared_error: 1.1744, scimark_benchmark: 939.5088, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.63, f_measure: 0.4786, kappa: 0.1856, kb_relative_information_score: 3.8956, mean_absolute_error: 0.319, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.437, predictive_accuracy: 0.5294, prior_entropy: 1.3486, recall: 0.5294, relative_absolute_error: 0.7848, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.5427, root_relative_squared_error: 1.1744, scimark_benchmark: 1330.2021,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.686, f_measure: 0.5325, kappa: 0.2788, kb_relative_information_score: 5.5347, mean_absolute_error: 0.2745, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.492, predictive_accuracy: 0.5882, prior_entropy: 1.3486, recall: 0.5882, relative_absolute_error: 0.6755, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.5236, root_relative_squared_error: 1.133, scimark_benchmark: 1308.3432, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7188, f_measure: 0.5745, kappa: 0.3239, kb_relative_information_score: 7.1259, mean_absolute_error: 0.2861, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.6415, predictive_accuracy: 0.5882, prior_entropy: 1.3486, recall: 0.5882, relative_absolute_error: 0.7041, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.4839, root_relative_squared_error: 1.0471, scimark_benchmark: 912.7324,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.596, f_measure: 0.5252, kappa: 0.2184, kb_relative_information_score: 4.9262, mean_absolute_error: 0.324, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.5882, predictive_accuracy: 0.5294, prior_entropy: 1.3486, recall: 0.5294, relative_absolute_error: 0.7973, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.5388, root_relative_squared_error: 1.1659, scimark_benchmark: 1331.5882,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7424, f_measure: 0.6375, kappa: 0.491, kb_relative_information_score: 8.519, mean_absolute_error: 0.1961, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.5815, predictive_accuracy: 0.7059, prior_entropy: 1.3486, recall: 0.7059, relative_absolute_error: 0.4825, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.4428, root_relative_squared_error: 0.9582, scimark_benchmark: 1298.4923, usercpu_time_millis: 290, usercpu_time_millis_training: 290,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5681, f_measure: 0.4241, kappa: 0.0727, kb_relative_information_score: 2.3474, mean_absolute_error: 0.3601, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.3904, predictive_accuracy: 0.4706, prior_entropy: 1.3486, recall: 0.4706, relative_absolute_error: 0.886, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.5547, root_relative_squared_error: 1.2003, scimark_benchmark: 1327.9121,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.63, f_measure: 0.4786, kappa: 0.1856, kb_relative_information_score: 3.8796, mean_absolute_error: 0.3424, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.437, predictive_accuracy: 0.5294, prior_entropy: 1.3486, recall: 0.5294, relative_absolute_error: 0.8424, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.49, root_relative_squared_error: 1.0603, scimark_benchmark: 1288.1375,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7306, f_measure: 0.5157, kappa: 0.3121, kb_relative_information_score: 5.5352, mean_absolute_error: 0.2745, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.4807, predictive_accuracy: 0.5882, prior_entropy: 1.3486, recall: 0.5882, relative_absolute_error: 0.6754, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.5098, root_relative_squared_error: 1.1031, scimark_benchmark: 1301.2156,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6791, f_measure: 0.5822, kappa: 0.3081, kb_relative_information_score: 6.7104, mean_absolute_error: 0.2745, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.6396, predictive_accuracy: 0.5882, prior_entropy: 1.3486, recall: 0.5882, relative_absolute_error: 0.6754, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.5239, root_relative_squared_error: 1.1337, scimark_benchmark: 1341.4232, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7045, f_measure: 0.4786, kappa: 0.1856, kb_relative_information_score: 2.7448, mean_absolute_error: 0.3532, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.437, predictive_accuracy: 0.5294, prior_entropy: 1.3486, recall: 0.5294, relative_absolute_error: 0.8691, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.4662, root_relative_squared_error: 1.0087, scimark_benchmark: 1337.6765, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6869, f_measure: 0.5852, kappa: 0.3892, kb_relative_information_score: 6.5989, mean_absolute_error: 0.2504, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.5345, predictive_accuracy: 0.6471, prior_entropy: 1.3486, recall: 0.6471, relative_absolute_error: 0.6161, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.4717, root_relative_squared_error: 1.0207, scimark_benchmark: 1320.4362, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6869, f_measure: 0.5852, kappa: 0.3892, kb_relative_information_score: 6.5989, mean_absolute_error: 0.2504, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.5345, predictive_accuracy: 0.6471, prior_entropy: 1.3486, recall: 0.6471, relative_absolute_error: 0.6161, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.4717, root_relative_squared_error: 1.0207, scimark_benchmark: 1294.7826, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.63, f_measure: 0.4786, kappa: 0.1856, kb_relative_information_score: 3.8956, mean_absolute_error: 0.319, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.437, predictive_accuracy: 0.5294, prior_entropy: 1.3486, recall: 0.5294, relative_absolute_error: 0.7848, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.5427, root_relative_squared_error: 1.1744, scimark_benchmark: 1386.5717,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7032, f_measure: 0.5852, kappa: 0.3892, kb_relative_information_score: 6.7153, mean_absolute_error: 0.2439, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.5345, predictive_accuracy: 0.6471, prior_entropy: 1.3486, recall: 0.6471, relative_absolute_error: 0.6, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.4654, root_relative_squared_error: 1.007, scimark_benchmark: 1330.7934,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6999, f_measure: 0.5852, kappa: 0.3892, kb_relative_information_score: 7.1512, mean_absolute_error: 0.2346, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.5345, predictive_accuracy: 0.6471, prior_entropy: 1.3486, recall: 0.6471, relative_absolute_error: 0.5773, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.4585, root_relative_squared_error: 0.9921, scimark_benchmark: 986.8456, usercpu_time_millis: 20, usercpu_time_millis_testing: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7311, f_measure: 0.4786, kappa: 0.1856, kb_relative_information_score: 3.5511, mean_absolute_error: 0.3315, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.437, predictive_accuracy: 0.5294, prior_entropy: 1.3486, recall: 0.5294, relative_absolute_error: 0.8158, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.4279, root_relative_squared_error: 0.9259, scimark_benchmark: 1352.1951, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4325, f_measure: 0.2293, kappa: -0.1525, kb_relative_information_score: -0.8813, mean_absolute_error: 0.4405, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.2118, predictive_accuracy: 0.2941, prior_entropy: 1.3486, recall: 0.2941, relative_absolute_error: 1.0838, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.6496, root_relative_squared_error: 1.4055, scimark_benchmark: 1341.994, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.596, f_measure: 0.4706, kappa: 0.2047, kb_relative_information_score: 4.0432, mean_absolute_error: 0.3137, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.4314, predictive_accuracy: 0.5294, prior_entropy: 1.3486, recall: 0.5294, relative_absolute_error: 0.7719, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.5601, root_relative_squared_error: 1.212, scimark_benchmark: 1358.4523, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5103, build_cpu_time: 0.005, build_memory: 628691296, f_measure: 0.3426, kappa: 0.0503, kb_relative_information_score: 0.2094, mean_absolute_error: 0.4129, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.371, predictive_accuracy: 0.4118, prior_entropy: 1.3486, recall: 0.4118, relative_absolute_error: 1.0159, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.5662, root_relative_squared_error: 1.2252, scimark_benchmark: 907.1899,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.759, build_cpu_time: 0.011, build_memory: 2703981552, f_measure: 0.5289, kappa: 0.2959, kb_relative_information_score: 5.4881, mean_absolute_error: 0.3095, mean_prior_absolute_error: 0.4064, number_of_instances: 17, precision: 0.482, predictive_accuracy: 0.5882, prior_entropy: 1.3486, recall: 0.5882, relative_absolute_error: 0.7615, root_mean_prior_squared_error: 0.4621, root_mean_squared_error: 0.417, root_relative_squared_error: 0.9023, scimark_benchmark: 943.8094,
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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