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File: /var/www/openml/index.php
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Function: require_once

OpenML
OpenML
Supervised Classification on diabetes_numeric

Supervised Classification on diabetes_numeric

Task 3656 Supervised Classification diabetes_numeric 558 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • 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: 0.5509, f_measure: 0.5847, kappa: 0.1419, kb_relative_information_score: 3.4285, mean_absolute_error: 0.4352, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.5904, predictive_accuracy: 0.5814, prior_entropy: 0.971, recall: 0.5814, relative_absolute_error: 0.9085, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.5357, root_relative_squared_error: 1.0957, scimark_benchmark: 939.5088,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4864, f_measure: 0.4651, kappa: -0.0249, kb_relative_information_score: -5.8918, mean_absolute_error: 0.5349, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.5077, predictive_accuracy: 0.4651, prior_entropy: 0.971, recall: 0.4651, relative_absolute_error: 1.1165, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.7314, root_relative_squared_error: 1.4958, scimark_benchmark: 889.3151, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4557, kb_relative_information_score: 6.8311, mean_absolute_error: 0.3953, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.3656, predictive_accuracy: 0.6047, prior_entropy: 0.971, recall: 0.6047, relative_absolute_error: 0.8252, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.6288, root_relative_squared_error: 1.286, scimark_benchmark: 887.6719,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4717, f_measure: 0.4656, kappa: -0.0652, kb_relative_information_score: 2.5901, mean_absolute_error: 0.4419, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.4554, predictive_accuracy: 0.5581, prior_entropy: 0.971, recall: 0.5581, relative_absolute_error: 0.9223, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.6647, root_relative_squared_error: 1.3595, scimark_benchmark: 1297.6599,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.681, f_measure: 0.6643, kappa: 0.2901, kb_relative_information_score: 5.25, mean_absolute_error: 0.4284, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.6665, predictive_accuracy: 0.6744, prior_entropy: 0.971, recall: 0.6744, relative_absolute_error: 0.8943, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.4769, root_relative_squared_error: 0.9754, scimark_benchmark: 1386.5717, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5407, f_measure: 0.5627, kappa: 0.0897, kb_relative_information_score: 6.8311, mean_absolute_error: 0.3953, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.5777, predictive_accuracy: 0.6047, prior_entropy: 0.971, recall: 0.6047, relative_absolute_error: 0.8252, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.6288, root_relative_squared_error: 1.286, scimark_benchmark: 942.6843,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6946, f_measure: 0.6643, kappa: 0.2901, kb_relative_information_score: 5.2774, mean_absolute_error: 0.4283, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.6665, predictive_accuracy: 0.6744, prior_entropy: 0.971, recall: 0.6744, relative_absolute_error: 0.8941, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.4718, root_relative_squared_error: 0.9649, scimark_benchmark: 869.6028, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4446, f_measure: 0.4943, kappa: -0.0591, kb_relative_information_score: 0.0126, mean_absolute_error: 0.4738, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.4875, predictive_accuracy: 0.5349, prior_entropy: 0.971, recall: 0.5349, relative_absolute_error: 0.989, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.5165, root_relative_squared_error: 1.0563, scimark_benchmark: 1073.494,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6029, f_measure: 0.6266, kappa: 0.2144, kb_relative_information_score: 6.8237, mean_absolute_error: 0.4094, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.6403, predictive_accuracy: 0.6512, prior_entropy: 0.971, recall: 0.6512, relative_absolute_error: 0.8546, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.4704, root_relative_squared_error: 0.9621, scimark_benchmark: 1250.8301,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6471, f_measure: 0.6527, kappa: 0.2777, kb_relative_information_score: 7.3644, mean_absolute_error: 0.3956, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.655, predictive_accuracy: 0.6512, prior_entropy: 0.971, recall: 0.6512, relative_absolute_error: 0.8257, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.5167, root_relative_squared_error: 1.0569, scimark_benchmark: 1066.7184,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.543, f_measure: 0.5601, kappa: 0.0851, kb_relative_information_score: 2.5901, mean_absolute_error: 0.4419, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.5627, predictive_accuracy: 0.5581, prior_entropy: 0.971, recall: 0.5581, relative_absolute_error: 0.9223, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.6647, root_relative_squared_error: 1.3595, scimark_benchmark: 1319.9043,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.733, f_measure: 0.6764, kappa: 0.3191, kb_relative_information_score: 10.2305, mean_absolute_error: 0.3704, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.6982, predictive_accuracy: 0.6977, prior_entropy: 0.971, recall: 0.6977, relative_absolute_error: 0.7731, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.4512, root_relative_squared_error: 0.9227, scimark_benchmark: 1316.0472,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6708, f_measure: 0.7055, kappa: 0.3783, kb_relative_information_score: 11.0453, mean_absolute_error: 0.3668, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.7221, predictive_accuracy: 0.7209, prior_entropy: 0.971, recall: 0.7209, relative_absolute_error: 0.7657, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.451, root_relative_squared_error: 0.9225, scimark_benchmark: 1327.6929,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6018, f_measure: 0.6086, kappa: 0.1976, kb_relative_information_score: 6.8311, mean_absolute_error: 0.3953, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.6183, predictive_accuracy: 0.6047, prior_entropy: 0.971, recall: 0.6047, relative_absolute_error: 0.8252, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.6288, root_relative_squared_error: 1.286, scimark_benchmark: 1359.379,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.224, kb_relative_information_score: -12.2533, mean_absolute_error: 0.6047, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.1563, predictive_accuracy: 0.3953, prior_entropy: 0.971, recall: 0.3953, relative_absolute_error: 1.2621, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.7776, root_relative_squared_error: 1.5903, scimark_benchmark: 1372.2145, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5882, f_measure: 0.6564, kappa: 0.2747, kb_relative_information_score: 6.1588, mean_absolute_error: 0.4159, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.6673, predictive_accuracy: 0.6744, prior_entropy: 0.971, recall: 0.6744, relative_absolute_error: 0.8681, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.51, root_relative_squared_error: 1.043, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6007, f_measure: 0.6232, kappa: 0.2055, kb_relative_information_score: 8.9516, mean_absolute_error: 0.3721, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.6212, predictive_accuracy: 0.6279, prior_entropy: 0.971, recall: 0.6279, relative_absolute_error: 0.7767, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.61, root_relative_squared_error: 1.2476, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4943, f_measure: 0.5138, kappa: -0.0112, kb_relative_information_score: -1.6508, mean_absolute_error: 0.4884, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.5165, predictive_accuracy: 0.5116, prior_entropy: 0.971, recall: 0.5116, relative_absolute_error: 1.0194, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.6988, root_relative_squared_error: 1.4293, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.388, f_measure: 0.4557, kb_relative_information_score: -0.3203, mean_absolute_error: 0.4811, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.3656, predictive_accuracy: 0.6047, prior_entropy: 0.971, recall: 0.6047, relative_absolute_error: 1.0043, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.491, root_relative_squared_error: 1.0043, scimark_benchmark: 1445.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.569, f_measure: 0.5955, kappa: 0.1527, kb_relative_information_score: 4.8904, mean_absolute_error: 0.428, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.6109, predictive_accuracy: 0.6279, prior_entropy: 0.971, recall: 0.6279, relative_absolute_error: 0.8933, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.5341, root_relative_squared_error: 1.0923, scimark_benchmark: 1384.4418,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.638, f_measure: 0.6279, kappa: 0.2217, kb_relative_information_score: 9.6616, mean_absolute_error: 0.3655, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.6279, predictive_accuracy: 0.6279, prior_entropy: 0.971, recall: 0.6279, relative_absolute_error: 0.763, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.5616, root_relative_squared_error: 1.1485, scimark_benchmark: 931.2336,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6437, f_measure: 0.6024, kappa: 0.1646, kb_relative_information_score: 8.8027, mean_absolute_error: 0.381, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.6008, predictive_accuracy: 0.6047, prior_entropy: 0.971, recall: 0.6047, relative_absolute_error: 0.7954, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.5387, root_relative_squared_error: 1.1018, scimark_benchmark: 945.6434,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6833, f_measure: 0.6232, kappa: 0.2055, kb_relative_information_score: 9.4711, mean_absolute_error: 0.3764, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.6212, predictive_accuracy: 0.6279, prior_entropy: 0.971, recall: 0.6279, relative_absolute_error: 0.7857, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.4942, root_relative_squared_error: 1.0107, scimark_benchmark: 941.7954, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7081, f_measure: 0.6703, kappa: 0.3049, kb_relative_information_score: 13.6083, mean_absolute_error: 0.3206, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.6691, predictive_accuracy: 0.6744, prior_entropy: 0.971, recall: 0.6744, relative_absolute_error: 0.6692, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.5556, root_relative_squared_error: 1.1363, scimark_benchmark: 936.7115, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.75, f_measure: 0.6643, kappa: 0.2901, kb_relative_information_score: 15.1601, mean_absolute_error: 0.3015, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.6665, predictive_accuracy: 0.6744, prior_entropy: 0.971, recall: 0.6744, relative_absolute_error: 0.6294, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.5189, root_relative_squared_error: 1.0612, scimark_benchmark: 936.6206, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7002, f_measure: 0.6643, kappa: 0.2901, kb_relative_information_score: 14.6612, mean_absolute_error: 0.31, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.6665, predictive_accuracy: 0.6744, prior_entropy: 0.971, recall: 0.6744, relative_absolute_error: 0.6472, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.5274, root_relative_squared_error: 1.0787, scimark_benchmark: 938.2848, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7183, f_measure: 0.6703, kappa: 0.3049, kb_relative_information_score: 12.9307, mean_absolute_error: 0.3302, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.6691, predictive_accuracy: 0.6744, prior_entropy: 0.971, recall: 0.6744, relative_absolute_error: 0.6893, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.5249, root_relative_squared_error: 1.0734, scimark_benchmark: 922.9039,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6629, f_measure: 0.646, kappa: 0.2586, kb_relative_information_score: 12.8534, mean_absolute_error: 0.3337, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.6726, predictive_accuracy: 0.6744, prior_entropy: 0.971, recall: 0.6744, relative_absolute_error: 0.6965, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.5217, root_relative_squared_error: 1.0671, scimark_benchmark: 938.9865,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6369, f_measure: 0.6703, kappa: 0.3049, kb_relative_information_score: 11.1034, mean_absolute_error: 0.35, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.6691, predictive_accuracy: 0.6744, prior_entropy: 0.971, recall: 0.6744, relative_absolute_error: 0.7306, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.5746, root_relative_squared_error: 1.1751, scimark_benchmark: 936.6206, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7025, f_measure: 0.6279, kappa: 0.2217, kb_relative_information_score: 10.7128, mean_absolute_error: 0.3518, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.6279, predictive_accuracy: 0.6279, prior_entropy: 0.971, recall: 0.6279, relative_absolute_error: 0.7344, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.53, root_relative_squared_error: 1.0839, scimark_benchmark: 924.6116,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.681, f_measure: 0.6492, kappa: 0.2629, kb_relative_information_score: 11.1294, mean_absolute_error: 0.3577, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.6479, predictive_accuracy: 0.6512, prior_entropy: 0.971, recall: 0.6512, relative_absolute_error: 0.7466, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.4811, root_relative_squared_error: 0.984, scimark_benchmark: 929.566,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6233, build_cpu_time: 0.0731, build_memory: 296562490.4186, f_measure: 0.5847, kappa: 0.1419, kb_relative_information_score: 5.95, mean_absolute_error: 0.4019, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.5904, predictive_accuracy: 0.5814, prior_entropy: 0.971, recall: 0.5814, relative_absolute_error: 0.8389, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.6178, root_relative_squared_error: 1.2635, scimark_benchmark: 937.9119,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5045, build_cpu_time: 0.4404, build_memory: 1622326680, f_measure: 0.5601, kappa: 0.0851, kb_relative_information_score: 1.0589, mean_absolute_error: 0.462, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.5627, predictive_accuracy: 0.5581, prior_entropy: 0.971, recall: 0.5581, relative_absolute_error: 0.9644, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.6005, root_relative_squared_error: 1.2282, scimark_benchmark: 938.6131,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, build_cpu_time: 0.3037, build_memory: 1438027072, f_measure: 0.5385, kappa: 0.0466, kb_relative_information_score: 0.5866, mean_absolute_error: 0.4663, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.5444, predictive_accuracy: 0.5349, prior_entropy: 0.971, recall: 0.5349, relative_absolute_error: 0.9734, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.6052, root_relative_squared_error: 1.2377, scimark_benchmark: 916.8903,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5747, build_cpu_time: 0.2144, build_memory: 698068975.814, f_measure: 0.5601, kappa: 0.0851, kb_relative_information_score: 2.3031, mean_absolute_error: 0.4446, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.5627, predictive_accuracy: 0.5581, prior_entropy: 0.971, recall: 0.5581, relative_absolute_error: 0.9281, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.5759, root_relative_squared_error: 1.1778, scimark_benchmark: 920.2874,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6086, build_cpu_time: 0.0081, build_memory: 55117255.6279, f_measure: 0.6279, kappa: 0.2217, kb_relative_information_score: 8.2023, mean_absolute_error: 0.381, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.6279, predictive_accuracy: 0.6279, prior_entropy: 0.971, recall: 0.6279, relative_absolute_error: 0.7952, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.6051, root_relative_squared_error: 1.2375, scimark_benchmark: 913.3372,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6335, build_cpu_time: 0.0149, build_memory: 256630847.2558, f_measure: 0.6024, kappa: 0.1646, kb_relative_information_score: 6.476, mean_absolute_error: 0.4003, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.6008, predictive_accuracy: 0.6047, prior_entropy: 0.971, recall: 0.6047, relative_absolute_error: 0.8355, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.6291, root_relative_squared_error: 1.2865, scimark_benchmark: 944.4197,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.612, build_cpu_time: 0.0362, build_memory: 1750684666.9767, f_measure: 0.5814, kappa: 0.1244, kb_relative_information_score: 5.0569, mean_absolute_error: 0.4135, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.5814, predictive_accuracy: 0.5814, prior_entropy: 0.971, recall: 0.5814, relative_absolute_error: 0.8631, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.6395, root_relative_squared_error: 1.3079, scimark_benchmark: 874.7324,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6097, build_cpu_time: 0.0881, build_memory: 155035557.7674, f_measure: 0.6064, kappa: 0.1814, kb_relative_information_score: 6.8135, mean_absolute_error: 0.3956, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.6088, predictive_accuracy: 0.6047, prior_entropy: 0.971, recall: 0.6047, relative_absolute_error: 0.8258, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.6287, root_relative_squared_error: 1.2859, scimark_benchmark: 937.9603,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5905, build_cpu_time: 0.1267, build_memory: 462818826.7907, f_measure: 0.5814, kappa: 0.1244, kb_relative_information_score: 4.7108, mean_absolute_error: 0.4186, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.5814, predictive_accuracy: 0.5814, prior_entropy: 0.971, recall: 0.5814, relative_absolute_error: 0.8738, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.647, root_relative_squared_error: 1.3232, scimark_benchmark: 937.279,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.56, build_cpu_time: 0.0062, build_memory: 326759621.5814, f_measure: 0.5556, kappa: 0.0663, kb_relative_information_score: 3.1493, mean_absolute_error: 0.4402, mean_prior_absolute_error: 0.4791, number_of_instances: 43, precision: 0.5537, predictive_accuracy: 0.5581, prior_entropy: 0.971, recall: 0.5581, relative_absolute_error: 0.9188, root_mean_prior_squared_error: 0.4889, root_mean_squared_error: 0.5747, root_relative_squared_error: 1.1753, scimark_benchmark: 945.0532,

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