OpenML
Supervised Classification on trains

Supervised Classification on trains

Task 51 Supervised Classification trains 693 runs submitted
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  • basic study_1 study_107 study_123 study_41 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8, f_measure: 0.899, kappa: 0.8, kb_relative_information_score: 6.3904, mean_absolute_error: 0.2, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.9167, predictive_accuracy: 0.9, prior_entropy: 1, recall: 0.9, relative_absolute_error: 0.4, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.3464, root_relative_squared_error: 0.6928, scimark_benchmark: 1339.4412,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 2.2401, mean_absolute_error: 0.3887, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.7773, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5538, root_relative_squared_error: 1.1076, scimark_benchmark: 1339.2472, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 2.2401, mean_absolute_error: 0.3887, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.7773, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5538, root_relative_squared_error: 1.1076, scimark_benchmark: 1362.9924,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 2.2401, mean_absolute_error: 0.3887, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.7773, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5538, root_relative_squared_error: 1.1076, scimark_benchmark: 1313.8988,
0 likes - 0 downloads - 0 reach - kappa: -1, kb_relative_information_score: -10, mean_absolute_error: 1, mean_prior_absolute_error: 0.5, number_of_instances: 10, prior_entropy: 1, relative_absolute_error: 2, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 1, root_relative_squared_error: 2, scimark_benchmark: 1349.1517,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.76, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 3.7466, mean_absolute_error: 0.3142, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.6283, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4896, root_relative_squared_error: 0.9792, scimark_benchmark: 908.2231,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 2.2401, mean_absolute_error: 0.3887, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.7773, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5538, root_relative_squared_error: 1.1076, scimark_benchmark: 908.2231,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 2.2401, mean_absolute_error: 0.3887, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.7773, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5538, root_relative_squared_error: 1.1076, scimark_benchmark: 1286.2211,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 2.2401, mean_absolute_error: 0.3887, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.7773, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5538, root_relative_squared_error: 1.1076, scimark_benchmark: 1338.5214,
0 likes - 0 downloads - 0 reach - kappa: -1, kb_relative_information_score: -10, mean_absolute_error: 1, mean_prior_absolute_error: 0.5, number_of_instances: 10, prior_entropy: 1, relative_absolute_error: 2, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 1, root_relative_squared_error: 2, scimark_benchmark: 1340.9749,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.76, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 3.7466, mean_absolute_error: 0.3142, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.6283, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4896, root_relative_squared_error: 0.9792, scimark_benchmark: 1346.2927,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 2.2401, mean_absolute_error: 0.3887, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.7773, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5538, root_relative_squared_error: 1.1076, scimark_benchmark: 930.5999,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 2.2401, mean_absolute_error: 0.3887, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.7773, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5538, root_relative_squared_error: 1.1076, scimark_benchmark: 1324.7884,
0 likes - 0 downloads - 0 reach - kappa: -1, kb_relative_information_score: -10, mean_absolute_error: 1, mean_prior_absolute_error: 0.5, number_of_instances: 10, prior_entropy: 1, relative_absolute_error: 2, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 1, root_relative_squared_error: 2, scimark_benchmark: 1338.5214,
0 likes - 0 downloads - 0 reach - kappa: -1, kb_relative_information_score: -10, mean_absolute_error: 1, mean_prior_absolute_error: 0.5, number_of_instances: 10, prior_entropy: 1, relative_absolute_error: 2, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 1, root_relative_squared_error: 2, scimark_benchmark: 1309.0674,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.76, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 3.7466, mean_absolute_error: 0.3142, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.6283, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4896, root_relative_squared_error: 0.9792, scimark_benchmark: 1349.1517,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 2.2401, mean_absolute_error: 0.3887, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.7773, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5538, root_relative_squared_error: 1.1076, scimark_benchmark: 1306.9281,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6, f_measure: 0.4949, kb_relative_information_score: 0.4986, mean_absolute_error: 0.4773, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.5, predictive_accuracy: 0.5, prior_entropy: 1, recall: 0.5, relative_absolute_error: 0.9545, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5089, root_relative_squared_error: 1.0178, scimark_benchmark: 1310.6554,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 3.4605, mean_absolute_error: 0.3295, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.659, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4554, root_relative_squared_error: 0.9108, scimark_benchmark: 1347.6543,
0 likes - 0 downloads - 0 reach - kappa: -1, kb_relative_information_score: -10, mean_absolute_error: 1, mean_prior_absolute_error: 0.5, number_of_instances: 10, prior_entropy: 1, relative_absolute_error: 2, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 1, root_relative_squared_error: 2, scimark_benchmark: 1318.4315, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 2.2401, mean_absolute_error: 0.3887, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.7773, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5538, root_relative_squared_error: 1.1076, scimark_benchmark: 1319.4538,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 2.2401, mean_absolute_error: 0.3887, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.7773, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5538, root_relative_squared_error: 1.1076, scimark_benchmark: 1319.4538,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 2.2401, mean_absolute_error: 0.3887, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.7773, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5538, root_relative_squared_error: 1.1076, scimark_benchmark: 1316.5668,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6, f_measure: 0.4949, kb_relative_information_score: 0.4986, mean_absolute_error: 0.4773, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.5, predictive_accuracy: 0.5, prior_entropy: 1, recall: 0.5, relative_absolute_error: 0.9545, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5089, root_relative_squared_error: 1.0178, scimark_benchmark: 1339.2472,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.76, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 3.7466, mean_absolute_error: 0.3142, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.6283, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4896, root_relative_squared_error: 0.9792, scimark_benchmark: 1326.2019, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 2.2401, mean_absolute_error: 0.3887, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.7773, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5538, root_relative_squared_error: 1.1076, scimark_benchmark: 1321.8321,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 2.2401, mean_absolute_error: 0.3887, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.7773, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5538, root_relative_squared_error: 1.1076, scimark_benchmark: 1342.2845,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 2.2401, mean_absolute_error: 0.3887, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.7773, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5538, root_relative_squared_error: 1.1076, scimark_benchmark: 1317.5348,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 3.4605, mean_absolute_error: 0.3295, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.659, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4554, root_relative_squared_error: 0.9108, scimark_benchmark: 1350.2591,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.56, f_measure: 0.4949, kb_relative_information_score: 0.7146, mean_absolute_error: 0.4656, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.5, predictive_accuracy: 0.5, prior_entropy: 1, recall: 0.5, relative_absolute_error: 0.9313, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4923, root_relative_squared_error: 0.9845, scimark_benchmark: 1320.8283, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.48, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 3.8646, mean_absolute_error: 0.309, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.618, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5483, root_relative_squared_error: 1.0965, scimark_benchmark: 1318.6467,
0 likes - 0 downloads - 0 reach - kappa: -1, kb_relative_information_score: -10, mean_absolute_error: 1, mean_prior_absolute_error: 0.5, number_of_instances: 10, prior_entropy: 1, relative_absolute_error: 2, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 1, root_relative_squared_error: 2, scimark_benchmark: 1345.9182, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 2.2401, mean_absolute_error: 0.3887, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.7773, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5538, root_relative_squared_error: 1.1076, scimark_benchmark: 1303.9481,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.24, f_measure: 0.2857, kappa: -0.2, kb_relative_information_score: -1.3636, mean_absolute_error: 0.5578, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.2222, predictive_accuracy: 0.4, prior_entropy: 1, recall: 0.4, relative_absolute_error: 1.1156, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.593, root_relative_squared_error: 1.1859, scimark_benchmark: 1371.174,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6, f_measure: 0.4949, kb_relative_information_score: 0.4986, mean_absolute_error: 0.4773, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.5, predictive_accuracy: 0.5, prior_entropy: 1, recall: 0.5, relative_absolute_error: 0.9545, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5089, root_relative_squared_error: 1.0178, scimark_benchmark: 1296.9979, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 2.2401, mean_absolute_error: 0.3887, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.7773, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5538, root_relative_squared_error: 1.1076, scimark_benchmark: 1313.8988,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8, f_measure: 0.899, kappa: 0.8, kb_relative_information_score: 6.3904, mean_absolute_error: 0.2, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.9167, predictive_accuracy: 0.9, prior_entropy: 1, recall: 0.9, relative_absolute_error: 0.4, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.3464, root_relative_squared_error: 0.6928, scimark_benchmark: 1344.0499,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.72, f_measure: 0.8, kappa: 0.6, kb_relative_information_score: 3.4475, mean_absolute_error: 0.3433, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.8, predictive_accuracy: 0.8, prior_entropy: 1, recall: 0.8, relative_absolute_error: 0.6867, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4478, root_relative_squared_error: 0.8957, scimark_benchmark: 1360.0477,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 4, mean_absolute_error: 0.3, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.6, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5477, root_relative_squared_error: 1.0954, scimark_benchmark: 1413.089,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, f_measure: 0.6, kappa: 0.2, kb_relative_information_score: 0.4809, mean_absolute_error: 0.4811, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.6, predictive_accuracy: 0.6, prior_entropy: 1, recall: 0.6, relative_absolute_error: 0.9622, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.493, root_relative_squared_error: 0.986, scimark_benchmark: 1413.089, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 4.2881, mean_absolute_error: 0.2894, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.5788, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4028, root_relative_squared_error: 0.8057, scimark_benchmark: 1413.089, usercpu_time_millis: 190, usercpu_time_millis_training: 190,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.72, f_measure: 0.7917, kappa: 0.6, kb_relative_information_score: 5.1082, mean_absolute_error: 0.2538, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.8571, predictive_accuracy: 0.8, prior_entropy: 1, recall: 0.8, relative_absolute_error: 0.5075, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4605, root_relative_squared_error: 0.9209, scimark_benchmark: 1348.8402,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.68, f_measure: 0.4949, kb_relative_information_score: 2.291, mean_absolute_error: 0.3851, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.5, predictive_accuracy: 0.5, prior_entropy: 1, recall: 0.5, relative_absolute_error: 0.7702, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5126, root_relative_squared_error: 1.0253, scimark_benchmark: 1419.2433,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6, f_measure: 0.6, kappa: 0.2, kb_relative_information_score: 1.725, mean_absolute_error: 0.4182, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.6, predictive_accuracy: 0.6, prior_entropy: 1, recall: 0.6, relative_absolute_error: 0.8364, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5793, root_relative_squared_error: 1.1585, scimark_benchmark: 1334.8495,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.68, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 2.6255, mean_absolute_error: 0.3834, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.7669, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4843, root_relative_squared_error: 0.9685, scimark_benchmark: 1367.8403,
0 likes - 0 downloads - 0 reach - kappa: -1, kb_relative_information_score: -1.2553, mean_absolute_error: 0.5455, mean_prior_absolute_error: 0.5, number_of_instances: 10, prior_entropy: 1, relative_absolute_error: 1.0909, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5455, root_relative_squared_error: 1.0909, scimark_benchmark: 1342.5243,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8, f_measure: 0.8, kappa: 0.6, kb_relative_information_score: 4.3152, mean_absolute_error: 0.3133, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.8, predictive_accuracy: 0.8, prior_entropy: 1, recall: 0.8, relative_absolute_error: 0.6267, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.368, root_relative_squared_error: 0.7361, scimark_benchmark: 1335.693,

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