OpenML
Supervised Classification on mbagrade

Supervised Classification on mbagrade

Task 3750 Supervised Classification mbagrade 520 runs submitted
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  • mythbusting_1 study_1 study_107 study_123 study_15 study_20 study_41 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5291, f_measure: 0.6003, kappa: 0.2278, kb_relative_information_score: 5.2848, mean_absolute_error: 0.4637, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6416, predictive_accuracy: 0.623, prior_entropy: 0.9984, recall: 0.623, relative_absolute_error: 0.9296, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.5069, root_relative_squared_error: 1.0151, scimark_benchmark: 1870.7932,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6487, f_measure: 0.571, kappa: 0.1903, kb_relative_information_score: 8.0022, mean_absolute_error: 0.4378, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6351, predictive_accuracy: 0.6066, prior_entropy: 0.9984, recall: 0.6066, relative_absolute_error: 0.8776, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4933, root_relative_squared_error: 0.9879, scimark_benchmark: 1870.7932,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5517, f_measure: 0.6065, kappa: 0.2304, kb_relative_information_score: 5.4163, mean_absolute_error: 0.4619, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6341, predictive_accuracy: 0.623, prior_entropy: 0.9984, recall: 0.623, relative_absolute_error: 0.926, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.492, root_relative_squared_error: 0.9852, scimark_benchmark: 1870.7932,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7214, f_measure: 0.6541, kappa: 0.3064, kb_relative_information_score: 11.4246, mean_absolute_error: 0.4148, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6556, predictive_accuracy: 0.6557, prior_entropy: 0.9984, recall: 0.6557, relative_absolute_error: 0.8316, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4572, root_relative_squared_error: 0.9154, scimark_benchmark: 1870.7932,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5345, f_measure: 0.6003, kappa: 0.2278, kb_relative_information_score: 5.1858, mean_absolute_error: 0.464, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6416, predictive_accuracy: 0.623, prior_entropy: 0.9984, recall: 0.623, relative_absolute_error: 0.9303, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.5063, root_relative_squared_error: 1.0138, scimark_benchmark: 1806.5905,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5313, f_measure: 0.5793, kappa: 0.1929, kb_relative_information_score: 5.6222, mean_absolute_error: 0.4572, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6249, predictive_accuracy: 0.6066, prior_entropy: 0.9984, recall: 0.6066, relative_absolute_error: 0.9165, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.5093, root_relative_squared_error: 1.0198, scimark_benchmark: 1806.5905,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5523, f_measure: 0.6065, kappa: 0.2304, kb_relative_information_score: 6.1423, mean_absolute_error: 0.4562, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6341, predictive_accuracy: 0.623, prior_entropy: 0.9984, recall: 0.623, relative_absolute_error: 0.9146, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.5146, root_relative_squared_error: 1.0305, scimark_benchmark: 1806.5905,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6859, f_measure: 0.6068, kappa: 0.2137, kb_relative_information_score: 12.5537, mean_absolute_error: 0.3969, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6083, predictive_accuracy: 0.6066, prior_entropy: 0.9984, recall: 0.6066, relative_absolute_error: 0.7957, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.5079, root_relative_squared_error: 1.0171, scimark_benchmark: 1806.5905, usercpu_time_millis: 15.6001, usercpu_time_millis_training: 15.6001,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5474, f_measure: 0.5922, kappa: 0.1982, kb_relative_information_score: 6.1294, mean_absolute_error: 0.4565, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6125, predictive_accuracy: 0.6066, prior_entropy: 0.9984, recall: 0.6066, relative_absolute_error: 0.9151, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.5165, root_relative_squared_error: 1.0342, scimark_benchmark: 1806.5905,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6422, f_measure: 0.5058, kappa: 0.0235, kb_relative_information_score: 11.7674, mean_absolute_error: 0.3995, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.5134, predictive_accuracy: 0.5082, prior_entropy: 0.9984, recall: 0.5082, relative_absolute_error: 0.801, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.5549, root_relative_squared_error: 1.1112, scimark_benchmark: 1806.5905,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5463, f_measure: 0.5922, kappa: 0.1982, kb_relative_information_score: 5.4407, mean_absolute_error: 0.4616, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6125, predictive_accuracy: 0.6066, prior_entropy: 0.9984, recall: 0.6066, relative_absolute_error: 0.9254, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4915, root_relative_squared_error: 0.9843, scimark_benchmark: 1877.5305,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.722, f_measure: 0.6554, kappa: 0.3087, kb_relative_information_score: 11.4929, mean_absolute_error: 0.4142, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6553, predictive_accuracy: 0.6557, prior_entropy: 0.9984, recall: 0.6557, relative_absolute_error: 0.8303, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4572, root_relative_squared_error: 0.9155, scimark_benchmark: 1850.8887,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4591, f_measure: 0.361, kb_relative_information_score: -0.1078, mean_absolute_error: 0.4994, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.2752, predictive_accuracy: 0.5246, prior_entropy: 0.9984, recall: 0.5246, relative_absolute_error: 1.0012, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.5, root_relative_squared_error: 1.0012, scimark_benchmark: 1850.8887,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5506, f_measure: 0.6067, kappa: 0.2577, kb_relative_information_score: 6.2675, mean_absolute_error: 0.4572, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6826, predictive_accuracy: 0.6393, prior_entropy: 0.9984, recall: 0.6393, relative_absolute_error: 0.9165, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4853, root_relative_squared_error: 0.9718, scimark_benchmark: 906.0979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6994, f_measure: 0.5882, kappa: 0.1743, kb_relative_information_score: 11.9059, mean_absolute_error: 0.4088, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.589, predictive_accuracy: 0.5902, prior_entropy: 0.9984, recall: 0.5902, relative_absolute_error: 0.8195, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4555, root_relative_squared_error: 0.9121, scimark_benchmark: 972.587,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6643, f_measure: 0.6007, kappa: 0.2035, kb_relative_information_score: 11.3853, mean_absolute_error: 0.4072, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6069, predictive_accuracy: 0.6066, prior_entropy: 0.9984, recall: 0.6066, relative_absolute_error: 0.8164, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4973, root_relative_squared_error: 0.9958, scimark_benchmark: 851.2074,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5506, f_measure: 0.6067, kappa: 0.2577, kb_relative_information_score: 6.028, mean_absolute_error: 0.4591, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6826, predictive_accuracy: 0.6393, prior_entropy: 0.9984, recall: 0.6393, relative_absolute_error: 0.9203, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4843, root_relative_squared_error: 0.9698, scimark_benchmark: 934.695,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6719, f_measure: 0.6491, kappa: 0.3019, kb_relative_information_score: 8.505, mean_absolute_error: 0.4391, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6604, predictive_accuracy: 0.6557, prior_entropy: 0.9984, recall: 0.6557, relative_absolute_error: 0.8803, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4776, root_relative_squared_error: 0.9563, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5506, f_measure: 0.6067, kappa: 0.2577, kb_relative_information_score: 6.028, mean_absolute_error: 0.4591, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6826, predictive_accuracy: 0.6393, prior_entropy: 0.9984, recall: 0.6393, relative_absolute_error: 0.9203, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4843, root_relative_squared_error: 0.9698, scimark_benchmark: 905.2959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6083, f_measure: 0.6143, kappa: 0.2602, kb_relative_information_score: 5.8965, mean_absolute_error: 0.4592, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.668, predictive_accuracy: 0.6393, prior_entropy: 0.9984, recall: 0.6393, relative_absolute_error: 0.9205, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4925, root_relative_squared_error: 0.9861, scimark_benchmark: 931.771, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4348, f_measure: 0.429, kappa: -0.1321, kb_relative_information_score: -7.2295, mean_absolute_error: 0.5574, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.4303, predictive_accuracy: 0.4426, prior_entropy: 0.9984, recall: 0.4426, relative_absolute_error: 1.1174, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.7466, root_relative_squared_error: 1.495, scimark_benchmark: 941.3847,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5506, f_measure: 0.6067, kappa: 0.2577, kb_relative_information_score: 6.028, mean_absolute_error: 0.4591, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6826, predictive_accuracy: 0.6393, prior_entropy: 0.9984, recall: 0.6393, relative_absolute_error: 0.9203, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4843, root_relative_squared_error: 0.9698, scimark_benchmark: 947.1781,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6083, f_measure: 0.6143, kappa: 0.2602, kb_relative_information_score: 5.8965, mean_absolute_error: 0.4592, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.668, predictive_accuracy: 0.6393, prior_entropy: 0.9984, recall: 0.6393, relative_absolute_error: 0.9205, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4925, root_relative_squared_error: 0.9861, scimark_benchmark: 936.3373, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6859, f_measure: 0.6068, kappa: 0.2137, kb_relative_information_score: 12.5537, mean_absolute_error: 0.3969, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6083, predictive_accuracy: 0.6066, prior_entropy: 0.9984, recall: 0.6066, relative_absolute_error: 0.7957, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.5079, root_relative_squared_error: 1.0171, scimark_benchmark: 947.1781, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5506, f_measure: 0.6067, kappa: 0.2577, kb_relative_information_score: 6.2675, mean_absolute_error: 0.4572, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6826, predictive_accuracy: 0.6393, prior_entropy: 0.9984, recall: 0.6393, relative_absolute_error: 0.9165, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4853, root_relative_squared_error: 0.9718, scimark_benchmark: 819.5729,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6994, f_measure: 0.5882, kappa: 0.1743, kb_relative_information_score: 11.9059, mean_absolute_error: 0.4088, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.589, predictive_accuracy: 0.5902, prior_entropy: 0.9984, recall: 0.5902, relative_absolute_error: 0.8195, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4555, root_relative_squared_error: 0.9121, scimark_benchmark: 901.6243, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6643, f_measure: 0.6007, kappa: 0.2035, kb_relative_information_score: 11.3853, mean_absolute_error: 0.4072, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6069, predictive_accuracy: 0.6066, prior_entropy: 0.9984, recall: 0.6066, relative_absolute_error: 0.8164, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4973, root_relative_squared_error: 0.9958, scimark_benchmark: 944.0133,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4348, f_measure: 0.429, kappa: -0.1321, kb_relative_information_score: -7.2295, mean_absolute_error: 0.5574, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.4303, predictive_accuracy: 0.4426, prior_entropy: 0.9984, recall: 0.4426, relative_absolute_error: 1.1174, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.7466, root_relative_squared_error: 1.495, scimark_benchmark: 937.5683,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5506, f_measure: 0.6067, kappa: 0.2577, kb_relative_information_score: 6.028, mean_absolute_error: 0.4591, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6826, predictive_accuracy: 0.6393, prior_entropy: 0.9984, recall: 0.6393, relative_absolute_error: 0.9203, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4843, root_relative_squared_error: 0.9698, scimark_benchmark: 938.1282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5506, f_measure: 0.6067, kappa: 0.2577, kb_relative_information_score: 6.028, mean_absolute_error: 0.4591, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6826, predictive_accuracy: 0.6393, prior_entropy: 0.9984, recall: 0.6393, relative_absolute_error: 0.9203, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4843, root_relative_squared_error: 0.9698, scimark_benchmark: 903.2737,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6719, f_measure: 0.6491, kappa: 0.3019, kb_relative_information_score: 8.505, mean_absolute_error: 0.4391, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6604, predictive_accuracy: 0.6557, prior_entropy: 0.9984, recall: 0.6557, relative_absolute_error: 0.8803, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4776, root_relative_squared_error: 0.9563, scimark_benchmark: 903.2737, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7171, f_measure: 0.6712, kappa: 0.3405, kb_relative_information_score: 11.825, mean_absolute_error: 0.4108, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6718, predictive_accuracy: 0.6721, prior_entropy: 0.9984, recall: 0.6721, relative_absolute_error: 0.8236, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4579, root_relative_squared_error: 0.9169, scimark_benchmark: 763.3895,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5506, f_measure: 0.6067, kappa: 0.2577, kb_relative_information_score: 6.028, mean_absolute_error: 0.4591, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6826, predictive_accuracy: 0.6393, prior_entropy: 0.9984, recall: 0.6393, relative_absolute_error: 0.9203, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4843, root_relative_squared_error: 0.9698, scimark_benchmark: 936.9595,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6859, f_measure: 0.6068, kappa: 0.2137, kb_relative_information_score: 12.5537, mean_absolute_error: 0.3969, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6083, predictive_accuracy: 0.6066, prior_entropy: 0.9984, recall: 0.6066, relative_absolute_error: 0.7957, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.5079, root_relative_squared_error: 1.0171, scimark_benchmark: 936.3213, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6762, f_measure: 0.6494, kappa: 0.3275, kb_relative_information_score: 11.5522, mean_absolute_error: 0.4156, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.711, predictive_accuracy: 0.6721, prior_entropy: 0.9984, recall: 0.6721, relative_absolute_error: 0.8331, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.456, root_relative_squared_error: 0.913, scimark_benchmark: 926.5462, usercpu_time_millis: 90, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.674, f_measure: 0.6494, kappa: 0.3275, kb_relative_information_score: 11.379, mean_absolute_error: 0.4172, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.711, predictive_accuracy: 0.6721, prior_entropy: 0.9984, recall: 0.6721, relative_absolute_error: 0.8364, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4564, root_relative_squared_error: 0.914, scimark_benchmark: 941.3057, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6778, f_measure: 0.6494, kappa: 0.3275, kb_relative_information_score: 10.9962, mean_absolute_error: 0.42, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.711, predictive_accuracy: 0.6721, prior_entropy: 0.9984, recall: 0.6721, relative_absolute_error: 0.842, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4573, root_relative_squared_error: 0.9157, scimark_benchmark: 939.3535, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7074, f_measure: 0.6494, kappa: 0.3275, kb_relative_information_score: 10.3623, mean_absolute_error: 0.4258, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.711, predictive_accuracy: 0.6721, prior_entropy: 0.9984, recall: 0.6721, relative_absolute_error: 0.8536, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4574, root_relative_squared_error: 0.9158, scimark_benchmark: 924.2305, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.674, f_measure: 0.6494, kappa: 0.3275, kb_relative_information_score: 11.0359, mean_absolute_error: 0.4192, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.711, predictive_accuracy: 0.6721, prior_entropy: 0.9984, recall: 0.6721, relative_absolute_error: 0.8403, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4628, root_relative_squared_error: 0.9267, scimark_benchmark: 899.1108, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5506, f_measure: 0.6067, kappa: 0.2577, kb_relative_information_score: 6.028, mean_absolute_error: 0.4591, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6826, predictive_accuracy: 0.6393, prior_entropy: 0.9984, recall: 0.6393, relative_absolute_error: 0.9203, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4843, root_relative_squared_error: 0.9698, scimark_benchmark: 1339.2472,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5506, f_measure: 0.6067, kappa: 0.2577, kb_relative_information_score: 6.028, mean_absolute_error: 0.4591, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6826, predictive_accuracy: 0.6393, prior_entropy: 0.9984, recall: 0.6393, relative_absolute_error: 0.9203, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4843, root_relative_squared_error: 0.9698, scimark_benchmark: 1362.9924,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5506, f_measure: 0.6067, kappa: 0.2577, kb_relative_information_score: 6.028, mean_absolute_error: 0.4591, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6826, predictive_accuracy: 0.6393, prior_entropy: 0.9984, recall: 0.6393, relative_absolute_error: 0.9203, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4843, root_relative_squared_error: 0.9698, scimark_benchmark: 1313.8988,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4348, f_measure: 0.429, kappa: -0.1321, kb_relative_information_score: -7.2295, mean_absolute_error: 0.5574, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.4303, predictive_accuracy: 0.4426, prior_entropy: 0.9984, recall: 0.4426, relative_absolute_error: 1.1174, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.7466, root_relative_squared_error: 1.495, scimark_benchmark: 1346.2927, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5506, f_measure: 0.6067, kappa: 0.2577, kb_relative_information_score: 6.028, mean_absolute_error: 0.4591, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6826, predictive_accuracy: 0.6393, prior_entropy: 0.9984, recall: 0.6393, relative_absolute_error: 0.9203, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4843, root_relative_squared_error: 0.9698, scimark_benchmark: 908.2231,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5506, f_measure: 0.6067, kappa: 0.2577, kb_relative_information_score: 6.028, mean_absolute_error: 0.4591, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6826, predictive_accuracy: 0.6393, prior_entropy: 0.9984, recall: 0.6393, relative_absolute_error: 0.9203, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4843, root_relative_squared_error: 0.9698, scimark_benchmark: 1338.5214,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7171, f_measure: 0.6712, kappa: 0.3405, kb_relative_information_score: 11.825, mean_absolute_error: 0.4108, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6718, predictive_accuracy: 0.6721, prior_entropy: 0.9984, recall: 0.6721, relative_absolute_error: 0.8236, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4579, root_relative_squared_error: 0.9169, scimark_benchmark: 1286.2211, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6859, f_measure: 0.6068, kappa: 0.2137, kb_relative_information_score: 12.5537, mean_absolute_error: 0.3969, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6083, predictive_accuracy: 0.6066, prior_entropy: 0.9984, recall: 0.6066, relative_absolute_error: 0.7957, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.5079, root_relative_squared_error: 1.0171, scimark_benchmark: 1393.8432, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6994, f_measure: 0.5882, kappa: 0.1743, kb_relative_information_score: 11.9059, mean_absolute_error: 0.4088, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.589, predictive_accuracy: 0.5902, prior_entropy: 0.9984, recall: 0.5902, relative_absolute_error: 0.8195, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4555, root_relative_squared_error: 0.9121, scimark_benchmark: 1336.0954,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4348, f_measure: 0.429, kappa: -0.1321, kb_relative_information_score: -7.2295, mean_absolute_error: 0.5574, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.4303, predictive_accuracy: 0.4426, prior_entropy: 0.9984, recall: 0.4426, relative_absolute_error: 1.1174, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.7466, root_relative_squared_error: 1.495, scimark_benchmark: 1333.202, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5506, f_measure: 0.6067, kappa: 0.2577, kb_relative_information_score: 6.028, mean_absolute_error: 0.4591, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6826, predictive_accuracy: 0.6393, prior_entropy: 0.9984, recall: 0.6393, relative_absolute_error: 0.9203, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4843, root_relative_squared_error: 0.9698, scimark_benchmark: 1340.9749,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5506, f_measure: 0.6067, kappa: 0.2577, kb_relative_information_score: 6.028, mean_absolute_error: 0.4591, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6826, predictive_accuracy: 0.6393, prior_entropy: 0.9984, recall: 0.6393, relative_absolute_error: 0.9203, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4843, root_relative_squared_error: 0.9698, scimark_benchmark: 1333.202,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5506, f_measure: 0.6067, kappa: 0.2577, kb_relative_information_score: 6.028, mean_absolute_error: 0.4591, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6826, predictive_accuracy: 0.6393, prior_entropy: 0.9984, recall: 0.6393, relative_absolute_error: 0.9203, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4843, root_relative_squared_error: 0.9698, scimark_benchmark: 1324.8408,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5506, f_measure: 0.6067, kappa: 0.2577, kb_relative_information_score: 6.028, mean_absolute_error: 0.4591, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6826, predictive_accuracy: 0.6393, prior_entropy: 0.9984, recall: 0.6393, relative_absolute_error: 0.9203, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4843, root_relative_squared_error: 0.9698, scimark_benchmark: 1333.202,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6719, f_measure: 0.6491, kappa: 0.3019, kb_relative_information_score: 8.505, mean_absolute_error: 0.4391, mean_prior_absolute_error: 0.4988, number_of_instances: 61, precision: 0.6604, predictive_accuracy: 0.6557, prior_entropy: 0.9984, recall: 0.6557, relative_absolute_error: 0.8803, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4776, root_relative_squared_error: 0.9563, scimark_benchmark: 1325.8468,

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