Task
Supervised Classification on diabetes

Supervised Classification on diabetes

Task 37 Supervised Classification diabetes 131577 runs submitted
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  • at2 basic mythbusting mythbusting_1 OpenML-CC18 OpenML100 study_1 study_107 study_123 study_14 study_15 study_20 study_29 study_30 study_41 study_7 study_70 study_73 study_98 study_99 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6517, f_measure: 0.6993, kappa: 0.324, kb_relative_information_score: 261.7115, mean_absolute_error: 0.2878, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7006, predictive_accuracy: 0.7122, prior_entropy: 0.9335, recall: 0.7122, relative_absolute_error: 0.6331, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5364, root_relative_squared_error: 1.1254, scimark_benchmark: 1982.4998,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8022, f_measure: 0.7329, kappa: 0.4004, kb_relative_information_score: 236.7875, mean_absolute_error: 0.3173, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7342, predictive_accuracy: 0.7422, prior_entropy: 0.9335, recall: 0.7422, relative_absolute_error: 0.6981, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4151, root_relative_squared_error: 0.871, scimark_benchmark: 2012.3083,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.497, f_measure: 0.5134, kb_relative_information_score: -0.1051, mean_absolute_error: 0.4545, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.4239, predictive_accuracy: 0.651, prior_entropy: 0.9335, recall: 0.651, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4766, root_relative_squared_error: 1, scimark_benchmark: 2007.5787,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6725, f_measure: 0.7006, kappa: 0.3363, kb_relative_information_score: 244.9883, mean_absolute_error: 0.2975, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.6988, predictive_accuracy: 0.7031, prior_entropy: 0.9335, recall: 0.7031, relative_absolute_error: 0.6545, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5441, root_relative_squared_error: 1.1415, scimark_benchmark: 2018.9505,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7443, f_measure: 0.7379, kappa: 0.4147, kb_relative_information_score: 241.2932, mean_absolute_error: 0.3145, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7369, predictive_accuracy: 0.7435, prior_entropy: 0.9335, recall: 0.7435, relative_absolute_error: 0.692, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4462, root_relative_squared_error: 0.9362, scimark_benchmark: 2010.8601,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8111, f_measure: 0.7507, kappa: 0.4479, kb_relative_information_score: 267.8873, mean_absolute_error: 0.295, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7496, predictive_accuracy: 0.7526, prior_entropy: 0.9335, recall: 0.7526, relative_absolute_error: 0.6492, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4165, root_relative_squared_error: 0.8737, scimark_benchmark: 2014.8151,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8114, f_measure: 0.7489, kappa: 0.4373, kb_relative_information_score: 261.5135, mean_absolute_error: 0.3008, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7499, predictive_accuracy: 0.7565, prior_entropy: 0.9335, recall: 0.7565, relative_absolute_error: 0.6618, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4106, root_relative_squared_error: 0.8614, scimark_benchmark: 2012.5052,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7759, f_measure: 0.7383, kappa: 0.4175, kb_relative_information_score: 271.7697, mean_absolute_error: 0.291, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7368, predictive_accuracy: 0.7422, prior_entropy: 0.9335, recall: 0.7422, relative_absolute_error: 0.6402, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.441, root_relative_squared_error: 0.9253, scimark_benchmark: 2017.2176,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5465, f_measure: 0.5981, kappa: 0.1232, kb_relative_information_score: 57.4514, mean_absolute_error: 0.4037, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.6018, predictive_accuracy: 0.5951, prior_entropy: 0.9335, recall: 0.5951, relative_absolute_error: 0.8882, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.6176, root_relative_squared_error: 1.2958, scimark_benchmark: 945.0391,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8065, f_measure: 0.7399, kappa: 0.4185, kb_relative_information_score: 240.4753, mean_absolute_error: 0.3142, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7393, predictive_accuracy: 0.7461, prior_entropy: 0.9335, recall: 0.7461, relative_absolute_error: 0.6914, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4148, root_relative_squared_error: 0.8702, scimark_benchmark: 935.9316,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7767, f_measure: 0.7334, kappa: 0.4042, kb_relative_information_score: 225.3836, mean_absolute_error: 0.3251, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7325, predictive_accuracy: 0.7396, prior_entropy: 0.9335, recall: 0.7396, relative_absolute_error: 0.7154, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4227, root_relative_squared_error: 0.8869, scimark_benchmark: 945.6479,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8136, f_measure: 0.7556, kappa: 0.4562, kb_relative_information_score: 278.7802, mean_absolute_error: 0.2878, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7544, predictive_accuracy: 0.7591, prior_entropy: 0.9335, recall: 0.7591, relative_absolute_error: 0.6331, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.421, root_relative_squared_error: 0.8833, scimark_benchmark: 918.4695,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7207, f_measure: 0.7655, kappa: 0.4724, kb_relative_information_score: 373.9013, mean_absolute_error: 0.224, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7726, predictive_accuracy: 0.776, prior_entropy: 0.9335, recall: 0.776, relative_absolute_error: 0.4928, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4732, root_relative_squared_error: 0.9929, scimark_benchmark: 941.7261,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7152, f_measure: 0.7616, kappa: 0.4633, kb_relative_information_score: 369.3221, mean_absolute_error: 0.2266, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7705, predictive_accuracy: 0.7734, prior_entropy: 0.9335, recall: 0.7734, relative_absolute_error: 0.4985, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.476, root_relative_squared_error: 0.9986, scimark_benchmark: 945.4756,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5134, kb_relative_information_score: 154.1008, mean_absolute_error: 0.349, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.4239, predictive_accuracy: 0.651, prior_entropy: 0.9335, recall: 0.651, relative_absolute_error: 0.7678, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5907, root_relative_squared_error: 1.2394, scimark_benchmark: 946.2775,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7114, f_measure: 0.7446, kappa: 0.4284, kb_relative_information_score: 189.1207, mean_absolute_error: 0.3538, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7446, predictive_accuracy: 0.7513, prior_entropy: 0.9335, recall: 0.7513, relative_absolute_error: 0.7784, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4354, root_relative_squared_error: 0.9136, scimark_benchmark: 894.1129,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7473, f_measure: 0.7395, kappa: 0.4199, kb_relative_information_score: 258.8417, mean_absolute_error: 0.302, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.738, predictive_accuracy: 0.7435, prior_entropy: 0.9335, recall: 0.7435, relative_absolute_error: 0.6645, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4439, root_relative_squared_error: 0.9314, scimark_benchmark: 947.082,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8351, f_measure: 0.7568, kappa: 0.4558, kb_relative_information_score: 253.4517, mean_absolute_error: 0.3098, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7571, predictive_accuracy: 0.763, prior_entropy: 0.9335, recall: 0.763, relative_absolute_error: 0.6815, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3948, root_relative_squared_error: 0.8283, scimark_benchmark: 947.7195,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.83, f_measure: 0.7692, kappa: 0.4829, kb_relative_information_score: 255.151, mean_absolute_error: 0.3101, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.771, predictive_accuracy: 0.776, prior_entropy: 0.9335, recall: 0.776, relative_absolute_error: 0.6823, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3963, root_relative_squared_error: 0.8315, scimark_benchmark: 918.7106,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.499, f_measure: 0.5128, kappa: -0.0026, kb_relative_information_score: 151.8113, mean_absolute_error: 0.3503, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.4236, predictive_accuracy: 0.6497, prior_entropy: 0.9335, recall: 0.6497, relative_absolute_error: 0.7707, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5918, root_relative_squared_error: 1.2417, scimark_benchmark: 911.468,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5518, f_measure: 0.5935, kappa: 0.1296, kb_relative_information_score: 211.3405, mean_absolute_error: 0.3164, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7323, predictive_accuracy: 0.6836, prior_entropy: 0.9335, recall: 0.6836, relative_absolute_error: 0.6962, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5625, root_relative_squared_error: 1.1801, scimark_benchmark: 909.0852,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7091, f_measure: 0.7538, kappa: 0.4463, kb_relative_information_score: 353.295, mean_absolute_error: 0.2357, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7591, predictive_accuracy: 0.7643, prior_entropy: 0.9335, recall: 0.7643, relative_absolute_error: 0.5186, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4855, root_relative_squared_error: 1.0185, scimark_benchmark: 944.1255,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8343, f_measure: 0.7574, kappa: 0.4578, kb_relative_information_score: 252.3979, mean_absolute_error: 0.3103, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7573, predictive_accuracy: 0.763, prior_entropy: 0.9335, recall: 0.763, relative_absolute_error: 0.6827, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3947, root_relative_squared_error: 0.8282, scimark_benchmark: 948.0166,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5491, f_measure: 0.6001, kappa: 0.1259, kb_relative_information_score: 62.1744, mean_absolute_error: 0.4008, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.6029, predictive_accuracy: 0.5977, prior_entropy: 0.9335, recall: 0.5977, relative_absolute_error: 0.8819, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.615, root_relative_squared_error: 1.2903, scimark_benchmark: 944.6124,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8125, f_measure: 0.7386, kappa: 0.4168, kb_relative_information_score: 257.6986, mean_absolute_error: 0.3021, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7373, predictive_accuracy: 0.7435, prior_entropy: 0.9335, recall: 0.7435, relative_absolute_error: 0.6648, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4139, root_relative_squared_error: 0.8683, scimark_benchmark: 916.9921,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.707, f_measure: 0.7451, kappa: 0.4288, kb_relative_information_score: 186.614, mean_absolute_error: 0.3557, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7457, predictive_accuracy: 0.7526, prior_entropy: 0.9335, recall: 0.7526, relative_absolute_error: 0.7826, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4342, root_relative_squared_error: 0.9109, scimark_benchmark: 912.0338,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8136, f_measure: 0.7556, kappa: 0.4562, kb_relative_information_score: 278.7802, mean_absolute_error: 0.2878, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7544, predictive_accuracy: 0.7591, prior_entropy: 0.9335, recall: 0.7591, relative_absolute_error: 0.6331, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.421, root_relative_squared_error: 0.8833, scimark_benchmark: 948.8101,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.723, f_measure: 0.7649, kappa: 0.4721, kb_relative_information_score: 369.3221, mean_absolute_error: 0.2266, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7686, predictive_accuracy: 0.7734, prior_entropy: 0.9335, recall: 0.7734, relative_absolute_error: 0.4985, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.476, root_relative_squared_error: 0.9986, scimark_benchmark: 944.5584,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8261, f_measure: 0.7572, kappa: 0.4545, kb_relative_information_score: 241.6435, mean_absolute_error: 0.319, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7617, predictive_accuracy: 0.7669, prior_entropy: 0.9335, recall: 0.7669, relative_absolute_error: 0.7019, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3987, root_relative_squared_error: 0.8365, scimark_benchmark: 910.3105,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8261, f_measure: 0.7572, kappa: 0.4545, kb_relative_information_score: 241.6435, mean_absolute_error: 0.319, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7617, predictive_accuracy: 0.7669, prior_entropy: 0.9335, recall: 0.7669, relative_absolute_error: 0.7019, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3987, root_relative_squared_error: 0.8365, scimark_benchmark: 948.0997,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8261, f_measure: 0.7572, kappa: 0.4545, kb_relative_information_score: 241.6435, mean_absolute_error: 0.319, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7617, predictive_accuracy: 0.7669, prior_entropy: 0.9335, recall: 0.7669, relative_absolute_error: 0.7019, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3987, root_relative_squared_error: 0.8365, scimark_benchmark: 948.4198,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7108, f_measure: 0.7545, kappa: 0.4484, kb_relative_information_score: 353.295, mean_absolute_error: 0.2357, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7588, predictive_accuracy: 0.7643, prior_entropy: 0.9335, recall: 0.7643, relative_absolute_error: 0.5186, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4855, root_relative_squared_error: 1.0185, scimark_benchmark: 946.6478,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7754, f_measure: 0.7393, kappa: 0.4164, kb_relative_information_score: 218.3343, mean_absolute_error: 0.3237, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.739, predictive_accuracy: 0.7461, prior_entropy: 0.9335, recall: 0.7461, relative_absolute_error: 0.7123, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4254, root_relative_squared_error: 0.8926, scimark_benchmark: 947.6424,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7343, f_measure: 0.6911, kappa: 0.3087, kb_relative_information_score: 218.3295, mean_absolute_error: 0.3163, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.689, predictive_accuracy: 0.6992, prior_entropy: 0.9335, recall: 0.6992, relative_absolute_error: 0.6959, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4869, root_relative_squared_error: 1.0215, scimark_benchmark: 946.8632,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.716, f_measure: 0.7518, kappa: 0.4464, kb_relative_information_score: 339.5575, mean_absolute_error: 0.2435, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7509, predictive_accuracy: 0.7565, prior_entropy: 0.9335, recall: 0.7565, relative_absolute_error: 0.5357, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4934, root_relative_squared_error: 1.0353, scimark_benchmark: 946.8771,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5134, kb_relative_information_score: 154.1008, mean_absolute_error: 0.349, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.4239, predictive_accuracy: 0.651, prior_entropy: 0.9335, recall: 0.651, relative_absolute_error: 0.7678, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5907, root_relative_squared_error: 1.2394, scimark_benchmark: 944.9917,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7539, f_measure: 0.7414, kappa: 0.422, kb_relative_information_score: 244.9031, mean_absolute_error: 0.3131, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7407, predictive_accuracy: 0.7474, prior_entropy: 0.9335, recall: 0.7474, relative_absolute_error: 0.689, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4387, root_relative_squared_error: 0.9205, scimark_benchmark: 943.7888,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7204, f_measure: 0.7506, kappa: 0.4397, kb_relative_information_score: 195.823, mean_absolute_error: 0.3513, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7544, predictive_accuracy: 0.7604, prior_entropy: 0.9335, recall: 0.7604, relative_absolute_error: 0.7728, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4266, root_relative_squared_error: 0.8951, scimark_benchmark: 907.7607,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7583, f_measure: 0.7424, kappa: 0.4228, kb_relative_information_score: 241.5785, mean_absolute_error: 0.316, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7429, predictive_accuracy: 0.75, prior_entropy: 0.9335, recall: 0.75, relative_absolute_error: 0.6954, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4365, root_relative_squared_error: 0.9158, scimark_benchmark: 923.728,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7828, f_measure: 0.7254, kappa: 0.3891, kb_relative_information_score: 236.827, mean_absolute_error: 0.3103, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7236, predictive_accuracy: 0.7292, prior_entropy: 0.9335, recall: 0.7292, relative_absolute_error: 0.6827, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4349, root_relative_squared_error: 0.9124, scimark_benchmark: 916.8263,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7137, f_measure: 0.7572, kappa: 0.4545, kb_relative_information_score: 357.8742, mean_absolute_error: 0.2331, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7617, predictive_accuracy: 0.7669, prior_entropy: 0.9335, recall: 0.7669, relative_absolute_error: 0.5128, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4828, root_relative_squared_error: 1.0129, scimark_benchmark: 944.769,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8325, f_measure: 0.7616, kappa: 0.4672, kb_relative_information_score: 253.558, mean_absolute_error: 0.3097, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7615, predictive_accuracy: 0.7669, prior_entropy: 0.9335, recall: 0.7669, relative_absolute_error: 0.6814, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3964, root_relative_squared_error: 0.8316, scimark_benchmark: 945.2707,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7157, f_measure: 0.755, kappa: 0.4514, kb_relative_information_score: 348.7158, mean_absolute_error: 0.2383, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7556, predictive_accuracy: 0.7617, prior_entropy: 0.9335, recall: 0.7617, relative_absolute_error: 0.5243, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4881, root_relative_squared_error: 1.0241, scimark_benchmark: 943.9592,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5134, kb_relative_information_score: 154.1008, mean_absolute_error: 0.349, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.4239, predictive_accuracy: 0.651, prior_entropy: 0.9335, recall: 0.651, relative_absolute_error: 0.7678, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5907, root_relative_squared_error: 1.2394, scimark_benchmark: 947.1255,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7802, f_measure: 0.7461, kappa: 0.4319, kb_relative_information_score: 230.8857, mean_absolute_error: 0.3245, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.746, predictive_accuracy: 0.7526, prior_entropy: 0.9335, recall: 0.7526, relative_absolute_error: 0.7139, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4191, root_relative_squared_error: 0.8794,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7145, f_measure: 0.7438, kappa: 0.427, kb_relative_information_score: 186.8913, mean_absolute_error: 0.3549, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7434, predictive_accuracy: 0.75, prior_entropy: 0.9335, recall: 0.75, relative_absolute_error: 0.7809, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4322, root_relative_squared_error: 0.9068,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8123, f_measure: 0.7432, kappa: 0.4266, kb_relative_information_score: 249.7737, mean_absolute_error: 0.3093, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7424, predictive_accuracy: 0.7487, prior_entropy: 0.9335, recall: 0.7487, relative_absolute_error: 0.6804, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4102, root_relative_squared_error: 0.8607, scimark_benchmark: 944.6294,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8327, f_measure: 0.7574, kappa: 0.4578, kb_relative_information_score: 251.2709, mean_absolute_error: 0.3108, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7573, predictive_accuracy: 0.763, prior_entropy: 0.9335, recall: 0.763, relative_absolute_error: 0.6839, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.396, root_relative_squared_error: 0.8309, scimark_benchmark: 948.9429,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7883, f_measure: 0.7524, kappa: 0.4484, kb_relative_information_score: 246.7055, mean_absolute_error: 0.3139, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7513, predictive_accuracy: 0.7565, prior_entropy: 0.9335, recall: 0.7565, relative_absolute_error: 0.6906, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4169, root_relative_squared_error: 0.8748, scimark_benchmark: 889.2309,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6643, f_measure: 0.712, kappa: 0.3522, kb_relative_information_score: 284.6074, mean_absolute_error: 0.2747, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7151, predictive_accuracy: 0.7253, prior_entropy: 0.9335, recall: 0.7253, relative_absolute_error: 0.6045, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5242, root_relative_squared_error: 1.0997, scimark_benchmark: 943.7743,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7188, f_measure: 0.7639, kappa: 0.4688, kb_relative_information_score: 371.6117, mean_absolute_error: 0.2253, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7713, predictive_accuracy: 0.7747, prior_entropy: 0.9335, recall: 0.7747, relative_absolute_error: 0.4956, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4746, root_relative_squared_error: 0.9958, scimark_benchmark: 948.6907,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7937, f_measure: 0.7317, kappa: 0.4124, kb_relative_information_score: 240.5837, mean_absolute_error: 0.3124, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7332, predictive_accuracy: 0.7305, prior_entropy: 0.9335, recall: 0.7305, relative_absolute_error: 0.6873, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4137, root_relative_squared_error: 0.8679, scimark_benchmark: 948.0111,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7883, f_measure: 0.7585, kappa: 0.463, kb_relative_information_score: 252.4855, mean_absolute_error: 0.3106, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7573, predictive_accuracy: 0.7617, prior_entropy: 0.9335, recall: 0.7617, relative_absolute_error: 0.6833, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4175, root_relative_squared_error: 0.8759, scimark_benchmark: 919.4881,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6548, f_measure: 0.7118, kappa: 0.3531, kb_relative_information_score: 314.372, mean_absolute_error: 0.2578, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7501, predictive_accuracy: 0.7422, prior_entropy: 0.9335, recall: 0.7422, relative_absolute_error: 0.5673, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5078, root_relative_squared_error: 1.0653, scimark_benchmark: 950.0279,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.514, f_measure: 0.5537, kappa: 0.0347, kb_relative_information_score: 142.6529, mean_absolute_error: 0.3555, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.585, predictive_accuracy: 0.6445, prior_entropy: 0.9335, recall: 0.6445, relative_absolute_error: 0.7821, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5962, root_relative_squared_error: 1.2509, scimark_benchmark: 948.0493,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6621, f_measure: 0.7084, kappa: 0.3447, kb_relative_information_score: 275.449, mean_absolute_error: 0.2799, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7095, predictive_accuracy: 0.7201, prior_entropy: 0.9335, recall: 0.7201, relative_absolute_error: 0.616, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5291, root_relative_squared_error: 1.1101, scimark_benchmark: 935.4081,

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