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OpenML
Task
Supervised Classification on rmftsa_sleepdata

Supervised Classification on rmftsa_sleepdata

Task 3607 Supervised Classification rmftsa_sleepdata 541 runs submitted
0 likes downloaded by 1 people , 1 total downloads 0 issues
Visibility: Public
  • mythbusting_1 study_1 study_107 study_15 study_20 study_41 study_7 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7797, f_measure: 0.6986, kappa: 0.3987, kb_relative_information_score: 340.0348, mean_absolute_error: 0.3421, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7012, predictive_accuracy: 0.6992, prior_entropy: 1, recall: 0.6992, relative_absolute_error: 0.6843, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4466, root_relative_squared_error: 0.8932, scimark_benchmark: 1325.2092, usercpu_time_millis: 50, usercpu_time_millis_testing: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7267, f_measure: 0.7216, kappa: 0.4541, kb_relative_information_score: 465.9724, mean_absolute_error: 0.2725, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7476, predictive_accuracy: 0.7275, prior_entropy: 1, recall: 0.7275, relative_absolute_error: 0.5449, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.522, root_relative_squared_error: 1.044, scimark_benchmark: 940.3347, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6086, f_measure: 0.5904, kappa: 0.2167, kb_relative_information_score: 219.9602, mean_absolute_error: 0.3926, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.6307, predictive_accuracy: 0.6074, prior_entropy: 1, recall: 0.6074, relative_absolute_error: 0.7852, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.6266, root_relative_squared_error: 1.2531, scimark_benchmark: 1333.5799, usercpu_time_millis: 710, usercpu_time_millis_testing: 130, usercpu_time_millis_training: 580,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.69, f_measure: 0.6869, kappa: 0.3796, kb_relative_information_score: 387.9685, mean_absolute_error: 0.3105, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.6967, predictive_accuracy: 0.6895, prior_entropy: 1, recall: 0.6895, relative_absolute_error: 0.6211, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5573, root_relative_squared_error: 1.1146, scimark_benchmark: 1386.5717, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7793, f_measure: 0.6909, kappa: 0.3853, kb_relative_information_score: 225.426, mean_absolute_error: 0.4043, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.6966, predictive_accuracy: 0.6924, prior_entropy: 1, recall: 0.6924, relative_absolute_error: 0.8086, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4471, root_relative_squared_error: 0.8943, scimark_benchmark: 1335.643, usercpu_time_millis: 110, usercpu_time_millis_training: 110,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4994, f_measure: 0.4951, kappa: -0.0012, kb_relative_information_score: -0.0506, mean_absolute_error: 0.5, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.4994, predictive_accuracy: 0.5, prior_entropy: 1, recall: 0.5, relative_absolute_error: 1, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.7071, root_relative_squared_error: 1.4142, scimark_benchmark: 938.343, usercpu_time_millis: 70, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7907, f_measure: 0.6889, kappa: 0.3792, kb_relative_information_score: 265.0587, mean_absolute_error: 0.3844, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.6913, predictive_accuracy: 0.6895, prior_entropy: 1, recall: 0.6895, relative_absolute_error: 0.7688, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4362, root_relative_squared_error: 0.8724, scimark_benchmark: 944.5495, usercpu_time_millis: 6490, usercpu_time_millis_testing: 190, usercpu_time_millis_training: 6300,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7507, f_measure: 0.7111, kappa: 0.4271, kb_relative_information_score: 279.4946, mean_absolute_error: 0.378, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7215, predictive_accuracy: 0.7139, prior_entropy: 1, recall: 0.7139, relative_absolute_error: 0.756, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4437, root_relative_squared_error: 0.8874, scimark_benchmark: 1073.494,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7638, f_measure: 0.7295, kappa: 0.4624, kb_relative_information_score: 294.2481, mean_absolute_error: 0.3712, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7374, predictive_accuracy: 0.7314, prior_entropy: 1, recall: 0.7314, relative_absolute_error: 0.7424, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4356, root_relative_squared_error: 0.8713, scimark_benchmark: 1325.2092,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7578, f_measure: 0.7153, kappa: 0.4349, kb_relative_information_score: 282.5039, mean_absolute_error: 0.3768, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7249, predictive_accuracy: 0.7178, prior_entropy: 1, recall: 0.7178, relative_absolute_error: 0.7536, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4418, root_relative_squared_error: 0.8837, scimark_benchmark: 1372.2145, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7831, f_measure: 0.7051, kappa: 0.4102, kb_relative_information_score: 353.1689, mean_absolute_error: 0.3347, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7052, predictive_accuracy: 0.7051, prior_entropy: 1, recall: 0.7051, relative_absolute_error: 0.6695, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4471, root_relative_squared_error: 0.8943, scimark_benchmark: 1331.6907, usercpu_time_millis: 140, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 110,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7677, f_measure: 0.6845, kappa: 0.3715, kb_relative_information_score: 355.2184, mean_absolute_error: 0.3324, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.6885, predictive_accuracy: 0.6855, prior_entropy: 1, recall: 0.6855, relative_absolute_error: 0.6648, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4592, root_relative_squared_error: 0.9184, scimark_benchmark: 1333.5799,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7761, f_measure: 0.7278, kappa: 0.4567, kb_relative_information_score: 309.735, mean_absolute_error: 0.3637, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7304, predictive_accuracy: 0.7285, prior_entropy: 1, recall: 0.7285, relative_absolute_error: 0.7274, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4362, root_relative_squared_error: 0.8724, scimark_benchmark: 1318.5526,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7736, f_measure: 0.7412, kappa: 0.4825, kb_relative_information_score: 320.8837, mean_absolute_error: 0.3603, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7415, predictive_accuracy: 0.7412, prior_entropy: 1, recall: 0.7412, relative_absolute_error: 0.7207, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4333, root_relative_squared_error: 0.8666, scimark_benchmark: 1330.2678, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6479, f_measure: 0.6458, kappa: 0.2962, kb_relative_information_score: 303.9644, mean_absolute_error: 0.3516, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.6524, predictive_accuracy: 0.6484, prior_entropy: 1, recall: 0.6484, relative_absolute_error: 0.7031, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5929, root_relative_squared_error: 1.1859, scimark_benchmark: 1291.6995, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5128, f_measure: 0.3705, kappa: 0.0258, kb_relative_information_score: 31.951, mean_absolute_error: 0.4844, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.6586, predictive_accuracy: 0.5156, prior_entropy: 1, recall: 0.5156, relative_absolute_error: 0.9688, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.696, root_relative_squared_error: 1.392, scimark_benchmark: 1335.4072,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7874, f_measure: 0.7475, kappa: 0.4964, kb_relative_information_score: 334.6577, mean_absolute_error: 0.3537, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7506, predictive_accuracy: 0.748, prior_entropy: 1, recall: 0.748, relative_absolute_error: 0.7074, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4264, root_relative_squared_error: 0.8527, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7, f_measure: 0.6999, kappa: 0.4002, kb_relative_information_score: 409.9696, mean_absolute_error: 0.2998, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7008, predictive_accuracy: 0.7002, prior_entropy: 1, recall: 0.7002, relative_absolute_error: 0.5996, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5475, root_relative_squared_error: 1.0951, scimark_benchmark: 1351.788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7085, f_measure: 0.7067, kappa: 0.4174, kb_relative_information_score: 427.9705, mean_absolute_error: 0.291, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7151, predictive_accuracy: 0.709, prior_entropy: 1, recall: 0.709, relative_absolute_error: 0.5821, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5395, root_relative_squared_error: 1.0789, scimark_benchmark: 1353.5686, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4967, f_measure: 0.3366, kb_relative_information_score: -0.0069, mean_absolute_error: 0.5, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.2529, predictive_accuracy: 0.5029, prior_entropy: 1, recall: 0.5029, relative_absolute_error: 1, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5, root_relative_squared_error: 1, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7788, f_measure: 0.7438, kappa: 0.4885, kb_relative_information_score: 326.0382, mean_absolute_error: 0.3588, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7456, predictive_accuracy: 0.7441, prior_entropy: 1, recall: 0.7441, relative_absolute_error: 0.7176, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4303, root_relative_squared_error: 0.8606, scimark_benchmark: 1384.4418,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7326, f_measure: 0.6875, kappa: 0.3816, kb_relative_information_score: 368.7465, mean_absolute_error: 0.3234, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.6988, predictive_accuracy: 0.6904, prior_entropy: 1, recall: 0.6904, relative_absolute_error: 0.6467, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5185, root_relative_squared_error: 1.0371, scimark_benchmark: 931.2336, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7272, f_measure: 0.6956, kappa: 0.3929, kb_relative_information_score: 283.9595, mean_absolute_error: 0.3752, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.6984, predictive_accuracy: 0.6963, prior_entropy: 1, recall: 0.6963, relative_absolute_error: 0.7505, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4652, root_relative_squared_error: 0.9305, scimark_benchmark: 932.3943,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7488, f_measure: 0.6957, kappa: 0.3929, kb_relative_information_score: 267.9234, mean_absolute_error: 0.3857, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.6981, predictive_accuracy: 0.6963, prior_entropy: 1, recall: 0.6963, relative_absolute_error: 0.7714, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4461, root_relative_squared_error: 0.8922, scimark_benchmark: 941.7954, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7488, f_measure: 0.6957, kappa: 0.3929, kb_relative_information_score: 267.9234, mean_absolute_error: 0.3857, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.6981, predictive_accuracy: 0.6963, prior_entropy: 1, recall: 0.6963, relative_absolute_error: 0.7714, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4461, root_relative_squared_error: 0.8922, scimark_benchmark: 923.7642, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7488, f_measure: 0.6957, kappa: 0.3929, kb_relative_information_score: 267.9234, mean_absolute_error: 0.3857, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.6981, predictive_accuracy: 0.6963, prior_entropy: 1, recall: 0.6963, relative_absolute_error: 0.7714, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4461, root_relative_squared_error: 0.8922, scimark_benchmark: 894.7455, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.769, f_measure: 0.7118, kappa: 0.429, kb_relative_information_score: 431.5973, mean_absolute_error: 0.2916, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7234, predictive_accuracy: 0.7148, prior_entropy: 1, recall: 0.7148, relative_absolute_error: 0.5833, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5014, root_relative_squared_error: 1.0028, scimark_benchmark: 894.7455, usercpu_time_millis: 140, usercpu_time_millis_training: 140,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7679, f_measure: 0.7216, kappa: 0.4485, kb_relative_information_score: 427.9179, mean_absolute_error: 0.2945, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.734, predictive_accuracy: 0.7246, prior_entropy: 1, recall: 0.7246, relative_absolute_error: 0.589, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4934, root_relative_squared_error: 0.9869, scimark_benchmark: 943.2817, usercpu_time_millis: 70, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7698, f_measure: 0.7151, kappa: 0.4349, kb_relative_information_score: 432.3931, mean_absolute_error: 0.2914, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7256, predictive_accuracy: 0.7178, prior_entropy: 1, recall: 0.7178, relative_absolute_error: 0.5827, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5009, root_relative_squared_error: 1.0018, scimark_benchmark: 942.1229, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7683, f_measure: 0.7216, kappa: 0.4485, kb_relative_information_score: 428.7852, mean_absolute_error: 0.2942, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.734, predictive_accuracy: 0.7246, prior_entropy: 1, recall: 0.7246, relative_absolute_error: 0.5884, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4927, root_relative_squared_error: 0.9854, scimark_benchmark: 922.9039, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7579, f_measure: 0.7206, kappa: 0.4466, kb_relative_information_score: 426.9309, mean_absolute_error: 0.2952, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7327, predictive_accuracy: 0.7236, prior_entropy: 1, recall: 0.7236, relative_absolute_error: 0.5904, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4945, root_relative_squared_error: 0.989, scimark_benchmark: 938.9865, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7799, f_measure: 0.7081, kappa: 0.4176, kb_relative_information_score: 304.1362, mean_absolute_error: 0.3651, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.711, predictive_accuracy: 0.709, prior_entropy: 1, recall: 0.709, relative_absolute_error: 0.7302, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4357, root_relative_squared_error: 0.8715, scimark_benchmark: 936.6206, usercpu_time_millis: 130, usercpu_time_millis_training: 130,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.78, f_measure: 0.7076, kappa: 0.4175, kb_relative_information_score: 299.8382, mean_absolute_error: 0.3677, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7125, predictive_accuracy: 0.709, prior_entropy: 1, recall: 0.709, relative_absolute_error: 0.7354, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.435, root_relative_squared_error: 0.8699, scimark_benchmark: 924.6116, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7771, f_measure: 0.7118, kappa: 0.429, kb_relative_information_score: 293.6784, mean_absolute_error: 0.3712, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7234, predictive_accuracy: 0.7148, prior_entropy: 1, recall: 0.7148, relative_absolute_error: 0.7424, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4364, root_relative_squared_error: 0.8729, scimark_benchmark: 924.6116, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8091, build_cpu_time: 37.639, build_memory: 877974517.5, f_measure: 0.7382, kappa: 0.4765, kb_relative_information_score: 365.2647, mean_absolute_error: 0.3343, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7384, predictive_accuracy: 0.7383, prior_entropy: 1, recall: 0.7383, relative_absolute_error: 0.6686, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4233, root_relative_squared_error: 0.8467, scimark_benchmark: 945.0532,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7915, build_cpu_time: 2.6775, build_memory: 153884566.8828, f_measure: 0.7186, kappa: 0.4374, kb_relative_information_score: 346.2646, mean_absolute_error: 0.3419, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.719, predictive_accuracy: 0.7188, prior_entropy: 1, recall: 0.7188, relative_absolute_error: 0.6838, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.436, root_relative_squared_error: 0.872, scimark_benchmark: 942.5053,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8089, build_cpu_time: 0.2984, build_memory: 755061782.5156, f_measure: 0.7244, kappa: 0.449, kb_relative_information_score: 359.8398, mean_absolute_error: 0.3358, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7251, predictive_accuracy: 0.7246, prior_entropy: 1, recall: 0.7246, relative_absolute_error: 0.6716, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4253, root_relative_squared_error: 0.8506, scimark_benchmark: 913.3372,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8086, build_cpu_time: 0.5179, build_memory: 303170651.7344, f_measure: 0.7282, kappa: 0.4568, kb_relative_information_score: 364.7404, mean_absolute_error: 0.3325, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7293, predictive_accuracy: 0.7285, prior_entropy: 1, recall: 0.7285, relative_absolute_error: 0.6651, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4259, root_relative_squared_error: 0.8519, scimark_benchmark: 944.4197,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8073, build_cpu_time: 1.0891, build_memory: 720196299.2891, f_measure: 0.7235, kappa: 0.4471, kb_relative_information_score: 364.5544, mean_absolute_error: 0.3327, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7238, predictive_accuracy: 0.7236, prior_entropy: 1, recall: 0.7236, relative_absolute_error: 0.6654, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.426, root_relative_squared_error: 0.8521, scimark_benchmark: 942.5053,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8055, build_cpu_time: 1.6904, build_memory: 848547807.6094, f_measure: 0.7293, kappa: 0.4588, kb_relative_information_score: 365.3152, mean_absolute_error: 0.3321, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7299, predictive_accuracy: 0.7295, prior_entropy: 1, recall: 0.7295, relative_absolute_error: 0.6643, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4271, root_relative_squared_error: 0.8543, scimark_benchmark: 937.9603,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.812, build_cpu_time: 0.1373, build_memory: 916979408.4609, f_measure: 0.7382, kappa: 0.4765, kb_relative_information_score: 358.3223, mean_absolute_error: 0.3384, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7384, predictive_accuracy: 0.7383, prior_entropy: 1, recall: 0.7383, relative_absolute_error: 0.6767, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4222, root_relative_squared_error: 0.8443, scimark_benchmark: 920.7965,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.812, build_cpu_time: 0.1101, build_memory: 1272708858.2969, f_measure: 0.7382, kappa: 0.4765, kb_relative_information_score: 358.3223, mean_absolute_error: 0.3384, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7384, predictive_accuracy: 0.7383, prior_entropy: 1, recall: 0.7383, relative_absolute_error: 0.6767, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4222, root_relative_squared_error: 0.8443, scimark_benchmark: 917.4547,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.812, build_cpu_time: 0.1573, build_memory: 909956464.6016, f_measure: 0.7382, kappa: 0.4765, kb_relative_information_score: 358.3223, mean_absolute_error: 0.3384, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7384, predictive_accuracy: 0.7383, prior_entropy: 1, recall: 0.7383, relative_absolute_error: 0.6767, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4222, root_relative_squared_error: 0.8443, scimark_benchmark: 939.0159,

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