Task
Supervised Classification on cholesterol

Supervised Classification on cholesterol

Task 3663 Supervised Classification cholesterol 516 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5139, f_measure: 0.5232, kappa: 0.0357, kb_relative_information_score: 4.5564, mean_absolute_error: 0.4883, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5226, predictive_accuracy: 0.5281, prior_entropy: 0.9935, recall: 0.5281, relative_absolute_error: 0.9856, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5381, root_relative_squared_error: 1.0811, scimark_benchmark: 1358.6198, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6098, f_measure: 0.619, kappa: 0.2298, kb_relative_information_score: 21.7202, mean_absolute_error: 0.4674, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.621, predictive_accuracy: 0.6238, prior_entropy: 0.9935, recall: 0.6238, relative_absolute_error: 0.9434, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4935, root_relative_squared_error: 0.9916, scimark_benchmark: 1313.11,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5987, f_measure: 0.6135, kappa: 0.2183, kb_relative_information_score: 18.018, mean_absolute_error: 0.472, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.6143, predictive_accuracy: 0.6172, prior_entropy: 0.9935, recall: 0.6172, relative_absolute_error: 0.9527, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4967, root_relative_squared_error: 0.9979, scimark_benchmark: 1327.3335,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5987, f_measure: 0.6135, kappa: 0.2183, kb_relative_information_score: 18.018, mean_absolute_error: 0.472, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.6143, predictive_accuracy: 0.6172, prior_entropy: 0.9935, recall: 0.6172, relative_absolute_error: 0.9527, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4967, root_relative_squared_error: 0.9979, scimark_benchmark: 1342.2845,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5987, f_measure: 0.6135, kappa: 0.2183, kb_relative_information_score: 18.018, mean_absolute_error: 0.472, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.6143, predictive_accuracy: 0.6172, prior_entropy: 0.9935, recall: 0.6172, relative_absolute_error: 0.9527, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4967, root_relative_squared_error: 0.9979, scimark_benchmark: 1331.1314,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5539, f_measure: 0.5229, kappa: 0.0368, kb_relative_information_score: 9.785, mean_absolute_error: 0.4805, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5235, predictive_accuracy: 0.5314, prior_entropy: 0.9935, recall: 0.5314, relative_absolute_error: 0.9699, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5089, root_relative_squared_error: 1.0225, scimark_benchmark: 1339.4412, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5989, f_measure: 0.6093, kappa: 0.21, kb_relative_information_score: 18.4235, mean_absolute_error: 0.4721, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.6108, predictive_accuracy: 0.6139, prior_entropy: 0.9935, recall: 0.6139, relative_absolute_error: 0.9529, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5008, root_relative_squared_error: 1.0063, scimark_benchmark: 1350.8432, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5454, f_measure: 0.541, kappa: 0.0726, kb_relative_information_score: 7.3655, mean_absolute_error: 0.4846, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5416, predictive_accuracy: 0.5479, prior_entropy: 0.9935, recall: 0.5479, relative_absolute_error: 0.9781, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5144, root_relative_squared_error: 1.0335, scimark_benchmark: 1330.9181, usercpu_time_millis: 80, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.556, f_measure: 0.5345, kappa: 0.0615, kb_relative_information_score: 7.6986, mean_absolute_error: 0.4844, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5366, predictive_accuracy: 0.5446, prior_entropy: 0.9935, recall: 0.5446, relative_absolute_error: 0.9778, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5025, root_relative_squared_error: 1.0095, scimark_benchmark: 1346.0226, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5476, f_measure: 0.5575, kappa: 0.1062, kb_relative_information_score: 22.9995, mean_absolute_error: 0.459, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5572, predictive_accuracy: 0.5578, prior_entropy: 0.9935, recall: 0.5578, relative_absolute_error: 0.9264, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5931, root_relative_squared_error: 1.1917, scimark_benchmark: 1321.4771, usercpu_time_millis: 60, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5139, f_measure: 0.5232, kappa: 0.0357, kb_relative_information_score: 4.5564, mean_absolute_error: 0.4883, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5226, predictive_accuracy: 0.5281, prior_entropy: 0.9935, recall: 0.5281, relative_absolute_error: 0.9856, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5381, root_relative_squared_error: 1.0811, scimark_benchmark: 1325.3966, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4676, f_measure: 0.4409, kappa: -0.0684, kb_relative_information_score: -5.0295, mean_absolute_error: 0.5017, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.4538, predictive_accuracy: 0.4984, prior_entropy: 0.9935, recall: 0.4984, relative_absolute_error: 1.0125, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.7083, root_relative_squared_error: 1.4231, scimark_benchmark: 1332.1612, usercpu_time_millis: 60, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4676, f_measure: 0.4409, kappa: -0.0684, kb_relative_information_score: -5.0295, mean_absolute_error: 0.5017, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.4538, predictive_accuracy: 0.4984, prior_entropy: 0.9935, recall: 0.4984, relative_absolute_error: 1.0125, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.7083, root_relative_squared_error: 1.4231, scimark_benchmark: 1320.1171, usercpu_time_millis: 60, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5987, f_measure: 0.6135, kappa: 0.2183, kb_relative_information_score: 18.018, mean_absolute_error: 0.472, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.6143, predictive_accuracy: 0.6172, prior_entropy: 0.9935, recall: 0.6172, relative_absolute_error: 0.9527, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4967, root_relative_squared_error: 0.9979, scimark_benchmark: 1333.9912, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5539, f_measure: 0.5229, kappa: 0.0368, kb_relative_information_score: 9.785, mean_absolute_error: 0.4805, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5235, predictive_accuracy: 0.5314, prior_entropy: 0.9935, recall: 0.5314, relative_absolute_error: 0.9699, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5089, root_relative_squared_error: 1.0225, scimark_benchmark: 1318.6096, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5987, f_measure: 0.6135, kappa: 0.2183, kb_relative_information_score: 18.018, mean_absolute_error: 0.472, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.6143, predictive_accuracy: 0.6172, prior_entropy: 0.9935, recall: 0.6172, relative_absolute_error: 0.9527, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4967, root_relative_squared_error: 0.9979, scimark_benchmark: 1342.6744,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5989, f_measure: 0.6093, kappa: 0.21, kb_relative_information_score: 18.4235, mean_absolute_error: 0.4721, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.6108, predictive_accuracy: 0.6139, prior_entropy: 0.9935, recall: 0.6139, relative_absolute_error: 0.9529, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5008, root_relative_squared_error: 1.0063, scimark_benchmark: 1357.8069, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5546, f_measure: 0.5879, kappa: 0.1673, kb_relative_information_score: 17.9611, mean_absolute_error: 0.4714, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5899, predictive_accuracy: 0.5941, prior_entropy: 0.9935, recall: 0.5941, relative_absolute_error: 0.9514, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5084, root_relative_squared_error: 1.0215, scimark_benchmark: 1313.8988,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5139, f_measure: 0.5232, kappa: 0.0357, kb_relative_information_score: 4.5564, mean_absolute_error: 0.4883, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5226, predictive_accuracy: 0.5281, prior_entropy: 0.9935, recall: 0.5281, relative_absolute_error: 0.9856, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5381, root_relative_squared_error: 1.0811, scimark_benchmark: 1260.1387, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4676, f_measure: 0.4409, kappa: -0.0684, kb_relative_information_score: -5.0295, mean_absolute_error: 0.5017, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.4538, predictive_accuracy: 0.4984, prior_entropy: 0.9935, recall: 0.4984, relative_absolute_error: 1.0125, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.7083, root_relative_squared_error: 1.4231, scimark_benchmark: 1371.174, usercpu_time_millis: 60, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 30,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4676, f_measure: 0.4409, kappa: -0.0684, kb_relative_information_score: -5.0295, mean_absolute_error: 0.5017, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.4538, predictive_accuracy: 0.4984, prior_entropy: 0.9935, recall: 0.4984, relative_absolute_error: 1.0125, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.7083, root_relative_squared_error: 1.4231, scimark_benchmark: 1360.6367, usercpu_time_millis: 50, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6098, f_measure: 0.619, kappa: 0.2298, kb_relative_information_score: 21.7202, mean_absolute_error: 0.4674, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.621, predictive_accuracy: 0.6238, prior_entropy: 0.9935, recall: 0.6238, relative_absolute_error: 0.9434, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4935, root_relative_squared_error: 0.9916, scimark_benchmark: 1260.1387,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5657, f_measure: 0.562, kappa: 0.1139, kb_relative_information_score: 16.0009, mean_absolute_error: 0.472, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5614, predictive_accuracy: 0.5644, prior_entropy: 0.9935, recall: 0.5644, relative_absolute_error: 0.9526, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5232, root_relative_squared_error: 1.0513, scimark_benchmark: 1341.5795, usercpu_time_millis: 2370, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 2350,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.556, f_measure: 0.5345, kappa: 0.0615, kb_relative_information_score: 7.6986, mean_absolute_error: 0.4844, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5366, predictive_accuracy: 0.5446, prior_entropy: 0.9935, recall: 0.5446, relative_absolute_error: 0.9778, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5025, root_relative_squared_error: 1.0095, scimark_benchmark: 1330.7266,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5198, f_measure: 0.5124, kappa: 0.0159, kb_relative_information_score: 8.869, mean_absolute_error: 0.4794, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5128, predictive_accuracy: 0.5215, prior_entropy: 0.9935, recall: 0.5215, relative_absolute_error: 0.9676, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.6068, root_relative_squared_error: 1.2192, scimark_benchmark: 1331.0755, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5139, f_measure: 0.5232, kappa: 0.0357, kb_relative_information_score: 4.5564, mean_absolute_error: 0.4883, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5226, predictive_accuracy: 0.5281, prior_entropy: 0.9935, recall: 0.5281, relative_absolute_error: 0.9856, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5381, root_relative_squared_error: 1.0811, scimark_benchmark: 1322.496, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5191, f_measure: 0.4901, kappa: -0.0312, kb_relative_information_score: 3.3532, mean_absolute_error: 0.4876, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.4891, predictive_accuracy: 0.4917, prior_entropy: 0.9935, recall: 0.4917, relative_absolute_error: 0.9841, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5351, root_relative_squared_error: 1.0752, scimark_benchmark: 1366.5423, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5546, f_measure: 0.5879, kappa: 0.1673, kb_relative_information_score: 17.9611, mean_absolute_error: 0.4714, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5899, predictive_accuracy: 0.5941, prior_entropy: 0.9935, recall: 0.5941, relative_absolute_error: 0.9514, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5084, root_relative_squared_error: 1.0215, scimark_benchmark: 918.6005,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.604, f_measure: 0.5731, kappa: 0.1368, kb_relative_information_score: 28.6236, mean_absolute_error: 0.4528, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5725, predictive_accuracy: 0.5743, prior_entropy: 0.9935, recall: 0.5743, relative_absolute_error: 0.9139, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5157, root_relative_squared_error: 1.0362, scimark_benchmark: 1301.9956, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6028, f_measure: 0.5731, kappa: 0.1368, kb_relative_information_score: 28.5081, mean_absolute_error: 0.4529, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5725, predictive_accuracy: 0.5743, prior_entropy: 0.9935, recall: 0.5743, relative_absolute_error: 0.914, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5159, root_relative_squared_error: 1.0365, scimark_benchmark: 1363.454,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5595, f_measure: 0.5454, kappa: 0.0854, kb_relative_information_score: 23.1964, mean_absolute_error: 0.4558, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.547, predictive_accuracy: 0.5446, prior_entropy: 0.9935, recall: 0.5446, relative_absolute_error: 0.9199, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.6724, root_relative_squared_error: 1.351, scimark_benchmark: 854.5188, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6271, f_measure: 0.6011, kappa: 0.2066, kb_relative_information_score: 0.1873, mean_absolute_error: 0.494, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.6098, predictive_accuracy: 0.6007, prior_entropy: 0.9935, recall: 0.6007, relative_absolute_error: 0.9971, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4993, root_relative_squared_error: 1.0031, scimark_benchmark: 1339.4189, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.508, f_measure: 0.4151, kappa: 0.0253, kb_relative_information_score: -4.042, mean_absolute_error: 0.4998, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.6651, predictive_accuracy: 0.5578, prior_entropy: 0.9935, recall: 0.5578, relative_absolute_error: 1.0088, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4998, root_relative_squared_error: 1.0043, scimark_benchmark: 932.0242,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.556, f_measure: 0.5345, kappa: 0.0615, kb_relative_information_score: 7.6986, mean_absolute_error: 0.4844, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5366, predictive_accuracy: 0.5446, prior_entropy: 0.9935, recall: 0.5446, relative_absolute_error: 0.9778, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5025, root_relative_squared_error: 1.0095, scimark_benchmark: 938.343, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.5124, kappa: 0.0191, kb_relative_information_score: -0.4856, mean_absolute_error: 0.4957, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5141, predictive_accuracy: 0.5116, prior_entropy: 0.9935, recall: 0.5116, relative_absolute_error: 1.0005, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5087, root_relative_squared_error: 1.0221, scimark_benchmark: 876.0664,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6079, f_measure: 0.5851, kappa: 0.1681, kb_relative_information_score: 36.1599, mean_absolute_error: 0.4396, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5886, predictive_accuracy: 0.5842, prior_entropy: 0.9935, recall: 0.5842, relative_absolute_error: 0.8873, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5457, root_relative_squared_error: 1.0965, scimark_benchmark: 1363.434,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.556, f_measure: 0.5345, kappa: 0.0615, kb_relative_information_score: 7.6986, mean_absolute_error: 0.4844, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5366, predictive_accuracy: 0.5446, prior_entropy: 0.9935, recall: 0.5446, relative_absolute_error: 0.9778, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5025, root_relative_squared_error: 1.0095, scimark_benchmark: 1299.5783, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5555, f_measure: 0.5415, kappa: 0.0724, kb_relative_information_score: 27.7899, mean_absolute_error: 0.448, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5408, predictive_accuracy: 0.5446, prior_entropy: 0.9935, recall: 0.5446, relative_absolute_error: 0.9042, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.6468, root_relative_squared_error: 1.2995, scimark_benchmark: 1312.3073, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5613, f_measure: 0.5415, kappa: 0.0854, kb_relative_information_score: 4.9794, mean_absolute_error: 0.489, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5523, predictive_accuracy: 0.5611, prior_entropy: 0.9935, recall: 0.5611, relative_absolute_error: 0.9871, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4984, root_relative_squared_error: 1.0013, scimark_benchmark: 934.1747, usercpu_time_millis: 130, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 120,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5777, f_measure: 0.5329, kappa: 0.0629, kb_relative_information_score: 8.2231, mean_absolute_error: 0.4846, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5384, predictive_accuracy: 0.5479, prior_entropy: 0.9935, recall: 0.5479, relative_absolute_error: 0.9781, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4974, root_relative_squared_error: 0.9993, scimark_benchmark: 889.3151, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5201, f_measure: 0.4896, kappa: -0.0325, kb_relative_information_score: 4.0087, mean_absolute_error: 0.4864, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.4884, predictive_accuracy: 0.4917, prior_entropy: 0.9935, recall: 0.4917, relative_absolute_error: 0.9817, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5469, root_relative_squared_error: 1.0988, scimark_benchmark: 1325.2092, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5414, f_measure: 0.5288, kappa: 0.0467, kb_relative_information_score: 9.0411, mean_absolute_error: 0.4816, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5279, predictive_accuracy: 0.5314, prior_entropy: 0.9935, recall: 0.5314, relative_absolute_error: 0.972, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5224, root_relative_squared_error: 1.0496, scimark_benchmark: 925.4974, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5766, f_measure: 0.5536, kappa: 0.0985, kb_relative_information_score: 11.6525, mean_absolute_error: 0.4792, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5551, predictive_accuracy: 0.5611, prior_entropy: 0.9935, recall: 0.5611, relative_absolute_error: 0.9671, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4996, root_relative_squared_error: 1.0038, scimark_benchmark: 1404.1865, usercpu_time_millis: 140, usercpu_time_millis_training: 140,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5626, f_measure: 0.52, kappa: 0.0307, kb_relative_information_score: 10.1758, mean_absolute_error: 0.4809, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5203, predictive_accuracy: 0.5281, prior_entropy: 0.9935, recall: 0.5281, relative_absolute_error: 0.9706, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5033, root_relative_squared_error: 1.0111, scimark_benchmark: 1315.395, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5539, f_measure: 0.5229, kappa: 0.0368, kb_relative_information_score: 9.785, mean_absolute_error: 0.4805, mean_prior_absolute_error: 0.4955, number_of_instances: 303, precision: 0.5235, predictive_accuracy: 0.5314, prior_entropy: 0.9935, recall: 0.5314, relative_absolute_error: 0.9699, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5089, root_relative_squared_error: 1.0225, scimark_benchmark: 889.3151, usercpu_time_millis: 30, usercpu_time_millis_training: 30,

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