OpenML
Supervised Classification on pasture

Supervised Classification on pasture

Task 3827 Supervised Classification pasture 483 runs submitted
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  • mythbusting_1 study_1 study_15 study_20 study_41 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6667, f_measure: 0.7152, kappa: 0.3478, kb_relative_information_score: 12.4641, mean_absolute_error: 0.2778, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.7128, predictive_accuracy: 0.7222, prior_entropy: 0.9268, recall: 0.7222, relative_absolute_error: 0.6209, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.527, root_relative_squared_error: 1.1178, scimark_benchmark: 1331.6907, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9028, f_measure: 0.8595, kappa: 0.6809, kb_relative_information_score: 19.4827, mean_absolute_error: 0.209, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.8594, predictive_accuracy: 0.8611, prior_entropy: 0.9268, recall: 0.8611, relative_absolute_error: 0.4672, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.3397, root_relative_squared_error: 0.7205, scimark_benchmark: 934.6432, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5333, kb_relative_information_score: 7.8212, mean_absolute_error: 0.3333, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.4444, predictive_accuracy: 0.6667, prior_entropy: 0.9268, recall: 0.6667, relative_absolute_error: 0.7451, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.5774, root_relative_squared_error: 1.2245, scimark_benchmark: 918.6491,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9427, f_measure: 0.8907, kappa: 0.76, kb_relative_information_score: 26.0927, mean_absolute_error: 0.1158, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.8983, predictive_accuracy: 0.8889, prior_entropy: 0.9268, recall: 0.8889, relative_absolute_error: 0.2589, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.3073, root_relative_squared_error: 0.6517, scimark_benchmark: 934.0566,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.941, f_measure: 0.9174, kappa: 0.8163, kb_relative_information_score: 26.2279, mean_absolute_error: 0.1201, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.9197, predictive_accuracy: 0.9167, prior_entropy: 0.9268, recall: 0.9167, relative_absolute_error: 0.2684, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.2913, root_relative_squared_error: 0.6178, scimark_benchmark: 1331.6907,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.941, f_measure: 0.9174, kappa: 0.8163, kb_relative_information_score: 25.9942, mean_absolute_error: 0.1194, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.9197, predictive_accuracy: 0.9167, prior_entropy: 0.9268, recall: 0.9167, relative_absolute_error: 0.2669, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.2929, root_relative_squared_error: 0.6211, scimark_benchmark: 914.4835,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8559, f_measure: 0.8291, kappa: 0.6087, kb_relative_information_score: 19.2604, mean_absolute_error: 0.2032, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.8308, predictive_accuracy: 0.8333, prior_entropy: 0.9268, recall: 0.8333, relative_absolute_error: 0.4541, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.3813, root_relative_squared_error: 0.8086, scimark_benchmark: 935.4444, usercpu_time_millis: 80, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9375, f_measure: 0.8861, kappa: 0.7391, kb_relative_information_score: 18.7694, mean_absolute_error: 0.2251, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.8897, predictive_accuracy: 0.8889, prior_entropy: 0.9268, recall: 0.8889, relative_absolute_error: 0.5032, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.3152, root_relative_squared_error: 0.6686, scimark_benchmark: 1330.0694, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6875, f_measure: 0.7395, kappa: 0.4, kb_relative_information_score: 14.7856, mean_absolute_error: 0.25, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.7407, predictive_accuracy: 0.75, prior_entropy: 0.9268, recall: 0.75, relative_absolute_error: 0.5588, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.5, root_relative_squared_error: 1.0605, scimark_benchmark: 1319.9043,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.599, f_measure: 0.6462, kappa: 0.1818, kb_relative_information_score: 6.4622, mean_absolute_error: 0.3539, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.6429, predictive_accuracy: 0.6667, prior_entropy: 0.9268, recall: 0.6667, relative_absolute_error: 0.791, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.5266, root_relative_squared_error: 1.1168, scimark_benchmark: 1318.5526,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8212, f_measure: 0.7778, kappa: 0.5, kb_relative_information_score: 16.7007, mean_absolute_error: 0.2292, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.7778, predictive_accuracy: 0.7778, prior_entropy: 0.9268, recall: 0.7778, relative_absolute_error: 0.5123, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4134, root_relative_squared_error: 0.8767, scimark_benchmark: 1327.6929,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8333, f_measure: 0.8595, kappa: 0.6809, kb_relative_information_score: 24.0713, mean_absolute_error: 0.1389, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.8594, predictive_accuracy: 0.8611, prior_entropy: 0.9268, recall: 0.8611, relative_absolute_error: 0.3105, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.3727, root_relative_squared_error: 0.7904, scimark_benchmark: 1372.2145,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.1667, kb_relative_information_score: -20.0361, mean_absolute_error: 0.6667, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.1111, predictive_accuracy: 0.3333, prior_entropy: 0.9268, recall: 0.3333, relative_absolute_error: 1.4902, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.8165, root_relative_squared_error: 1.7318, scimark_benchmark: 1308.9788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8247, f_measure: 0.8624, kappa: 0.6939, kb_relative_information_score: 23.0412, mean_absolute_error: 0.1563, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.8651, predictive_accuracy: 0.8611, prior_entropy: 0.9268, recall: 0.8611, relative_absolute_error: 0.3493, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.3694, root_relative_squared_error: 0.7835, scimark_benchmark: 1358.4523,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6667, f_measure: 0.7152, kappa: 0.3478, kb_relative_information_score: 12.4641, mean_absolute_error: 0.2778, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.7128, predictive_accuracy: 0.7222, prior_entropy: 0.9268, recall: 0.7222, relative_absolute_error: 0.6209, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.527, root_relative_squared_error: 1.1178, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.625, f_measure: 0.6667, kappa: 0.25, kb_relative_information_score: 7.8212, mean_absolute_error: 0.3333, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.6667, predictive_accuracy: 0.6667, prior_entropy: 0.9268, recall: 0.6667, relative_absolute_error: 0.7451, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.5774, root_relative_squared_error: 1.2245, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3889, f_measure: 0.5333, kb_relative_information_score: -0.402, mean_absolute_error: 0.4499, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.4444, predictive_accuracy: 0.6667, prior_entropy: 0.9268, recall: 0.6667, relative_absolute_error: 1.0056, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4739, root_relative_squared_error: 1.0052, scimark_benchmark: 1505.597,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8142, f_measure: 0.8333, kappa: 0.625, kb_relative_information_score: 21.3639, mean_absolute_error: 0.1735, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.8333, predictive_accuracy: 0.8333, prior_entropy: 0.9268, recall: 0.8333, relative_absolute_error: 0.3877, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.3975, root_relative_squared_error: 0.8432, scimark_benchmark: 1384.4418,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.849, f_measure: 0.8074, kappa: 0.5714, kb_relative_information_score: 19.5761, mean_absolute_error: 0.1922, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.8105, predictive_accuracy: 0.8056, prior_entropy: 0.9268, recall: 0.8056, relative_absolute_error: 0.4296, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4313, root_relative_squared_error: 0.9147, scimark_benchmark: 931.2336, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8056, f_measure: 0.8074, kappa: 0.5714, kb_relative_information_score: 19.384, mean_absolute_error: 0.1952, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.8105, predictive_accuracy: 0.8056, prior_entropy: 0.9268, recall: 0.8056, relative_absolute_error: 0.4364, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.441, root_relative_squared_error: 0.9353, scimark_benchmark: 945.6434, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8177, f_measure: 0.7778, kappa: 0.5, kb_relative_information_score: 17.4299, mean_absolute_error: 0.2174, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.7778, predictive_accuracy: 0.7778, prior_entropy: 0.9268, recall: 0.7778, relative_absolute_error: 0.486, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4587, root_relative_squared_error: 0.9729, scimark_benchmark: 941.7954, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7795, f_measure: 0.7471, kappa: 0.4255, kb_relative_information_score: 14.6925, mean_absolute_error: 0.2516, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.7455, predictive_accuracy: 0.75, prior_entropy: 0.9268, recall: 0.75, relative_absolute_error: 0.5625, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4976, root_relative_squared_error: 1.0554, scimark_benchmark: 923.7642, usercpu_time_millis: 90, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7413, f_measure: 0.7471, kappa: 0.4255, kb_relative_information_score: 14.0198, mean_absolute_error: 0.2615, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.7455, predictive_accuracy: 0.75, prior_entropy: 0.9268, recall: 0.75, relative_absolute_error: 0.5845, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.5034, root_relative_squared_error: 1.0676, scimark_benchmark: 894.7455, usercpu_time_millis: 160, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 110,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8073, f_measure: 0.8333, kappa: 0.625, kb_relative_information_score: 21.7499, mean_absolute_error: 0.1667, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.8333, predictive_accuracy: 0.8333, prior_entropy: 0.9268, recall: 0.8333, relative_absolute_error: 0.3725, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4082, root_relative_squared_error: 0.8659, scimark_benchmark: 940.2922, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7969, f_measure: 0.8333, kappa: 0.625, kb_relative_information_score: 21.7467, mean_absolute_error: 0.1667, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.8333, predictive_accuracy: 0.8333, prior_entropy: 0.9268, recall: 0.8333, relative_absolute_error: 0.3727, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4082, root_relative_squared_error: 0.8659, scimark_benchmark: 943.2817, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8524, f_measure: 0.8333, kappa: 0.625, kb_relative_information_score: 21.7102, mean_absolute_error: 0.1674, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.8333, predictive_accuracy: 0.8333, prior_entropy: 0.9268, recall: 0.8333, relative_absolute_error: 0.3741, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.408, root_relative_squared_error: 0.8654, scimark_benchmark: 942.1229, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8924, f_measure: 0.7778, kappa: 0.5, kb_relative_information_score: 17.6733, mean_absolute_error: 0.2144, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.7778, predictive_accuracy: 0.7778, prior_entropy: 0.9268, recall: 0.7778, relative_absolute_error: 0.4793, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4526, root_relative_squared_error: 0.96, scimark_benchmark: 936.6206, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8785, f_measure: 0.8033, kappa: 0.5532, kb_relative_information_score: 19.4438, mean_absolute_error: 0.1942, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.8024, predictive_accuracy: 0.8056, prior_entropy: 0.9268, recall: 0.8056, relative_absolute_error: 0.4341, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4373, root_relative_squared_error: 0.9276, scimark_benchmark: 938.4278,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9219, f_measure: 0.8553, kappa: 0.6667, kb_relative_information_score: 24.0652, mean_absolute_error: 0.139, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.8642, predictive_accuracy: 0.8611, prior_entropy: 0.9268, recall: 0.8611, relative_absolute_error: 0.3107, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.3723, root_relative_squared_error: 0.7897, scimark_benchmark: 938.4285, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9063, f_measure: 0.8033, kappa: 0.5532, kb_relative_information_score: 19.4685, mean_absolute_error: 0.1951, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.8024, predictive_accuracy: 0.8056, prior_entropy: 0.9268, recall: 0.8056, relative_absolute_error: 0.4362, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4234, root_relative_squared_error: 0.8981, scimark_benchmark: 924.6116, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8924, f_measure: 0.7395, kappa: 0.4, kb_relative_information_score: 16.657, mean_absolute_error: 0.2243, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.7407, predictive_accuracy: 0.75, prior_entropy: 0.9268, recall: 0.75, relative_absolute_error: 0.5013, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4534, root_relative_squared_error: 0.9617, scimark_benchmark: 924.6116, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9045, f_measure: 0.7395, kappa: 0.4, kb_relative_information_score: 16.9811, mean_absolute_error: 0.2221, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.7407, predictive_accuracy: 0.75, prior_entropy: 0.9268, recall: 0.75, relative_absolute_error: 0.4965, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4344, root_relative_squared_error: 0.9213, scimark_benchmark: 947.9494,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8819, f_measure: 0.7395, kappa: 0.4, kb_relative_information_score: 15.4022, mean_absolute_error: 0.239, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.7407, predictive_accuracy: 0.75, prior_entropy: 0.9268, recall: 0.75, relative_absolute_error: 0.5343, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4303, root_relative_squared_error: 0.9126, scimark_benchmark: 929.566,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3889, f_measure: 0.5333, kb_relative_information_score: -0.402, mean_absolute_error: 0.4499, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.4444, predictive_accuracy: 0.6667, prior_entropy: 0.9268, recall: 0.6667, relative_absolute_error: 1.0056, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4739, root_relative_squared_error: 1.0052, scimark_benchmark: 938.9865,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8194, f_measure: 0.6762, kappa: 0.3333, kb_relative_information_score: 11.5769, mean_absolute_error: 0.2846, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.7222, predictive_accuracy: 0.6667, prior_entropy: 0.9268, recall: 0.6667, relative_absolute_error: 0.6362, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4685, root_relative_squared_error: 0.9937, scimark_benchmark: 934.5243,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8889, f_measure: 0.7778, kappa: 0.5, kb_relative_information_score: 17.8478, mean_absolute_error: 0.2112, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.7778, predictive_accuracy: 0.7778, prior_entropy: 0.9268, recall: 0.7778, relative_absolute_error: 0.472, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4273, root_relative_squared_error: 0.9062, scimark_benchmark: 933.8635,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.941, f_measure: 0.8595, kappa: 0.6809, kb_relative_information_score: 21.2114, mean_absolute_error: 0.1903, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.8594, predictive_accuracy: 0.8611, prior_entropy: 0.9268, recall: 0.8611, relative_absolute_error: 0.4253, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.3014, root_relative_squared_error: 0.6393, scimark_benchmark: 943.6956,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3889, f_measure: 0.5333, kb_relative_information_score: -0.402, mean_absolute_error: 0.4499, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.4444, predictive_accuracy: 0.6667, prior_entropy: 0.9268, recall: 0.6667, relative_absolute_error: 1.0056, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4739, root_relative_squared_error: 1.0052, scimark_benchmark: 929.566,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7465, f_measure: 0.7012, kappa: 0.3529, kb_relative_information_score: 8.9568, mean_absolute_error: 0.3228, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.7175, predictive_accuracy: 0.6944, prior_entropy: 0.9268, recall: 0.6944, relative_absolute_error: 0.7216, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4786, root_relative_squared_error: 1.0151, scimark_benchmark: 911.0478, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8316, build_cpu_time: 0.4838, build_memory: 703363499.3333, f_measure: 0.8074, kappa: 0.5714, kb_relative_information_score: 20.1779, mean_absolute_error: 0.1832, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.8105, predictive_accuracy: 0.8056, prior_entropy: 0.9268, recall: 0.8056, relative_absolute_error: 0.4096, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4171, root_relative_squared_error: 0.8847, scimark_benchmark: 919.5971,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8351, build_cpu_time: 0.0303, build_memory: 969150675.5556, f_measure: 0.7778, kappa: 0.5, kb_relative_information_score: 17.3641, mean_absolute_error: 0.2182, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.7778, predictive_accuracy: 0.7778, prior_entropy: 0.9268, recall: 0.7778, relative_absolute_error: 0.4878, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4576, root_relative_squared_error: 0.9705, scimark_benchmark: 945.5885,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8351, build_cpu_time: 0.0246, build_memory: 890946941.1111, f_measure: 0.7778, kappa: 0.5, kb_relative_information_score: 17.3641, mean_absolute_error: 0.2182, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.7778, predictive_accuracy: 0.7778, prior_entropy: 0.9268, recall: 0.7778, relative_absolute_error: 0.4878, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4576, root_relative_squared_error: 0.9705, scimark_benchmark: 930.5854,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.816, build_cpu_time: 0.0089, build_memory: 1324810899.7778, f_measure: 0.7523, kappa: 0.449, kb_relative_information_score: 14.3012, mean_absolute_error: 0.2547, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.7559, predictive_accuracy: 0.75, prior_entropy: 0.9268, recall: 0.75, relative_absolute_error: 0.5694, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4839, root_relative_squared_error: 1.0264, scimark_benchmark: 939.0159,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8611, build_cpu_time: 0.0031, build_memory: 1379502226.6667, f_measure: 0.8333, kappa: 0.625, kb_relative_information_score: 21.1163, mean_absolute_error: 0.1762, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.8333, predictive_accuracy: 0.8333, prior_entropy: 0.9268, recall: 0.8333, relative_absolute_error: 0.3939, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4111, root_relative_squared_error: 0.8719, scimark_benchmark: 943.4039,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8021, build_cpu_time: 0.0061, build_memory: 1030235648.6667, f_measure: 0.8333, kappa: 0.625, kb_relative_information_score: 21.1517, mean_absolute_error: 0.1756, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.8333, predictive_accuracy: 0.8333, prior_entropy: 0.9268, recall: 0.8333, relative_absolute_error: 0.3925, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4116, root_relative_squared_error: 0.873, scimark_benchmark: 906.6607,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7743, build_cpu_time: 0.0096, build_memory: 1142439852.6667, f_measure: 0.8333, kappa: 0.625, kb_relative_information_score: 21.1517, mean_absolute_error: 0.1756, mean_prior_absolute_error: 0.4474, number_of_instances: 36, precision: 0.8333, predictive_accuracy: 0.8333, prior_entropy: 0.9268, recall: 0.8333, relative_absolute_error: 0.3925, root_mean_prior_squared_error: 0.4715, root_mean_squared_error: 0.4116, root_relative_squared_error: 0.873, scimark_benchmark: 923.9118,

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