OpenML
Supervised Classification on rmftsa_sleepdata

Supervised Classification on rmftsa_sleepdata

Task 3607 Supervised Classification rmftsa_sleepdata 541 runs submitted
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  • 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: 0.7823, build_cpu_time: 0.0408, build_memory: 356897331.1016, f_measure: 0.7099, kappa: 0.42, kb_relative_information_score: 356.7554, mean_absolute_error: 0.3329, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7103, predictive_accuracy: 0.71, prior_entropy: 1, recall: 0.71, relative_absolute_error: 0.6659, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4482, root_relative_squared_error: 0.8964, scimark_benchmark: 943.4766,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7832, build_cpu_time: 0.08, build_memory: 162108611.2891, f_measure: 0.7051, kappa: 0.4102, kb_relative_information_score: 355.6278, mean_absolute_error: 0.3337, 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: 0.6675, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4472, root_relative_squared_error: 0.8944, scimark_benchmark: 946.5543,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7825, build_cpu_time: 0.12, build_memory: 2536545062.3047, f_measure: 0.7021, kappa: 0.4043, kb_relative_information_score: 352.8487, mean_absolute_error: 0.3349, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7022, predictive_accuracy: 0.7021, prior_entropy: 1, recall: 0.7021, relative_absolute_error: 0.6699, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4474, root_relative_squared_error: 0.8948, scimark_benchmark: 941.3608,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7875, build_cpu_time: 8.9484, build_memory: 2015403674.5313, f_measure: 0.7031, kappa: 0.4064, kb_relative_information_score: 351.2617, mean_absolute_error: 0.3368, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7034, predictive_accuracy: 0.7031, prior_entropy: 1, recall: 0.7031, relative_absolute_error: 0.6737, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4409, root_relative_squared_error: 0.8818, scimark_benchmark: 934.7581,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7883, build_cpu_time: 4.3891, build_memory: 583347300.3125, f_measure: 0.7089, kappa: 0.4181, kb_relative_information_score: 353.8942, mean_absolute_error: 0.3357, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7094, predictive_accuracy: 0.709, prior_entropy: 1, recall: 0.709, relative_absolute_error: 0.6714, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4408, root_relative_squared_error: 0.8816, scimark_benchmark: 940.5606,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7873, build_cpu_time: 2.4082, build_memory: 604152120.5938, f_measure: 0.7117, kappa: 0.424, kb_relative_information_score: 354.2144, mean_absolute_error: 0.3352, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7127, predictive_accuracy: 0.7119, prior_entropy: 1, recall: 0.7119, relative_absolute_error: 0.6704, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4421, root_relative_squared_error: 0.8842, scimark_benchmark: 930.267,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.79, build_cpu_time: 1.6599, build_memory: 672107459.4766, f_measure: 0.7109, kappa: 0.422, kb_relative_information_score: 359.2521, mean_absolute_error: 0.3327, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7113, predictive_accuracy: 0.7109, prior_entropy: 1, recall: 0.7109, relative_absolute_error: 0.6654, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4403, root_relative_squared_error: 0.8806, scimark_benchmark: 785.9104,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.79, build_cpu_time: 1.0646, build_memory: 1179692377.25, f_measure: 0.7109, kappa: 0.422, kb_relative_information_score: 359.2521, mean_absolute_error: 0.3327, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7113, predictive_accuracy: 0.7109, prior_entropy: 1, recall: 0.7109, relative_absolute_error: 0.6654, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4403, root_relative_squared_error: 0.8806, scimark_benchmark: 942.3187,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7533, build_cpu_time: 0.0029, build_memory: 1796655895.7109, f_measure: 0.7069, kappa: 0.4139, kb_relative_information_score: 412.5768, mean_absolute_error: 0.3, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7072, predictive_accuracy: 0.707, prior_entropy: 1, recall: 0.707, relative_absolute_error: 0.6, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4958, root_relative_squared_error: 0.9915, scimark_benchmark: 942.3187,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7533, build_cpu_time: 0.005, build_memory: 789760885.6328, f_measure: 0.7069, kappa: 0.4139, kb_relative_information_score: 412.5768, mean_absolute_error: 0.3, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7072, predictive_accuracy: 0.707, prior_entropy: 1, recall: 0.707, relative_absolute_error: 0.6, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4958, root_relative_squared_error: 0.9915, scimark_benchmark: 940.6012,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7533, build_cpu_time: 0.0048, build_memory: 549087033.75, f_measure: 0.7069, kappa: 0.4139, kb_relative_information_score: 412.5768, mean_absolute_error: 0.3, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7072, predictive_accuracy: 0.707, prior_entropy: 1, recall: 0.707, relative_absolute_error: 0.6, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4958, root_relative_squared_error: 0.9915, scimark_benchmark: 941.6532,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7533, build_cpu_time: 0.0038, build_memory: 893768428.2891, f_measure: 0.7069, kappa: 0.4139, kb_relative_information_score: 412.5768, mean_absolute_error: 0.3, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7072, predictive_accuracy: 0.707, prior_entropy: 1, recall: 0.707, relative_absolute_error: 0.6, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4958, root_relative_squared_error: 0.9915, scimark_benchmark: 902.1764,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7575, build_cpu_time: 0.0088, build_memory: 645012552.2813, f_measure: 0.7059, kappa: 0.412, kb_relative_information_score: 409.4574, mean_absolute_error: 0.3018, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7063, predictive_accuracy: 0.7061, prior_entropy: 1, recall: 0.7061, relative_absolute_error: 0.6035, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4924, root_relative_squared_error: 0.9849, scimark_benchmark: 938.3567,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7582, build_cpu_time: 0.0108, build_memory: 259364124.4688, f_measure: 0.7077, kappa: 0.4158, kb_relative_information_score: 408.9476, mean_absolute_error: 0.302, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7086, predictive_accuracy: 0.708, prior_entropy: 1, recall: 0.708, relative_absolute_error: 0.6041, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4911, root_relative_squared_error: 0.9822, scimark_benchmark: 938.3567,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7628, build_cpu_time: 0.0431, build_memory: 1153565402.5156, f_measure: 0.7105, kappa: 0.4216, kb_relative_information_score: 406.4629, mean_absolute_error: 0.3036, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7119, predictive_accuracy: 0.7109, prior_entropy: 1, recall: 0.7109, relative_absolute_error: 0.6072, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4872, root_relative_squared_error: 0.9745, scimark_benchmark: 939.4327,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8007, build_cpu_time: 0.0706, build_memory: 276461569.0859, f_measure: 0.75, kappa: 0.5001, kb_relative_information_score: 324.0148, mean_absolute_error: 0.361, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7503, predictive_accuracy: 0.75, prior_entropy: 1, recall: 0.75, relative_absolute_error: 0.722, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4233, root_relative_squared_error: 0.8465, scimark_benchmark: 947.2295,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7657, build_cpu_time: 0.0827, build_memory: 238017643.7109, f_measure: 0.6876, kappa: 0.3816, kb_relative_information_score: 245.2057, mean_absolute_error: 0.3923, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.6985, predictive_accuracy: 0.6904, prior_entropy: 1, recall: 0.6904, relative_absolute_error: 0.7846, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4554, root_relative_squared_error: 0.9108, scimark_benchmark: 939.6798,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7785, build_cpu_time: 0.0193, build_memory: 51207445.3906, f_measure: 0.691, kappa: 0.3852, kb_relative_information_score: 234.6283, mean_absolute_error: 0.3996, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.6964, predictive_accuracy: 0.6924, prior_entropy: 1, recall: 0.6924, relative_absolute_error: 0.7991, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4471, root_relative_squared_error: 0.8941, scimark_benchmark: 945.5725,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7643, build_cpu_time: 0.0041, build_memory: 255739909.0156, f_measure: 0.6855, kappa: 0.3777, kb_relative_information_score: 244.7306, mean_absolute_error: 0.3924, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.6968, predictive_accuracy: 0.6885, prior_entropy: 1, recall: 0.6885, relative_absolute_error: 0.7848, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.456, root_relative_squared_error: 0.912, scimark_benchmark: 942.5344,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8121, build_cpu_time: 48.6866, build_memory: 3001835839.9063, f_measure: 0.732, kappa: 0.4663, kb_relative_information_score: 335.965, mean_absolute_error: 0.3503, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7378, predictive_accuracy: 0.7334, prior_entropy: 1, recall: 0.7334, relative_absolute_error: 0.7007, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4201, root_relative_squared_error: 0.8403, scimark_benchmark: 942.728,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8115, build_cpu_time: 117.7727, build_memory: 1646339723.2578, f_measure: 0.7329, kappa: 0.4683, kb_relative_information_score: 334.1262, mean_absolute_error: 0.3512, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7389, predictive_accuracy: 0.7344, prior_entropy: 1, recall: 0.7344, relative_absolute_error: 0.7024, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4204, root_relative_squared_error: 0.8408, scimark_benchmark: 941.5509,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.791, build_cpu_time: 0.0382, build_memory: 253040315.6484, f_measure: 0.7217, kappa: 0.4486, kb_relative_information_score: 279.4343, mean_absolute_error: 0.3808, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7336, predictive_accuracy: 0.7246, prior_entropy: 1, recall: 0.7246, relative_absolute_error: 0.7616, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4318, root_relative_squared_error: 0.8637, scimark_benchmark: 942.9616,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7909, build_cpu_time: 0.0251, build_memory: 1415484025.3359, f_measure: 0.7197, kappa: 0.4446, kb_relative_information_score: 280.2694, mean_absolute_error: 0.3803, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7315, predictive_accuracy: 0.7227, prior_entropy: 1, recall: 0.7227, relative_absolute_error: 0.7607, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4316, root_relative_squared_error: 0.8632, scimark_benchmark: 940.8364,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7189, build_cpu_time: 0.492, build_memory: 116354378.5, f_measure: 0.6924, kappa: 0.3892, kb_relative_information_score: 292.8252, mean_absolute_error: 0.3677, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7001, predictive_accuracy: 0.6943, prior_entropy: 1, recall: 0.6943, relative_absolute_error: 0.7354, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4819, root_relative_squared_error: 0.9639, scimark_benchmark: 942.728,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7895, build_cpu_time: 0.0077, build_memory: 1190046140.2969, f_measure: 0.7235, kappa: 0.4525, kb_relative_information_score: 286.1079, mean_absolute_error: 0.3776, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.736, predictive_accuracy: 0.7266, prior_entropy: 1, recall: 0.7266, relative_absolute_error: 0.7553, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4318, root_relative_squared_error: 0.8636, scimark_benchmark: 938.259,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7817, build_cpu_time: 0.0036, build_memory: 3369461970.6875, f_measure: 0.7231, kappa: 0.4524, kb_relative_information_score: 283.6686, mean_absolute_error: 0.3787, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7376, predictive_accuracy: 0.7266, prior_entropy: 1, recall: 0.7266, relative_absolute_error: 0.7575, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4338, root_relative_squared_error: 0.8677, scimark_benchmark: 944.9147,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8078, build_cpu_time: 2.1049, build_memory: 1868231628.1797, f_measure: 0.7383, kappa: 0.4765, kb_relative_information_score: 345.0983, mean_absolute_error: 0.3465, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7383, predictive_accuracy: 0.7383, prior_entropy: 1, recall: 0.7383, relative_absolute_error: 0.6931, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4211, root_relative_squared_error: 0.8423, scimark_benchmark: 876.9475,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8096, build_cpu_time: 5.322, build_memory: 216642085.1172, f_measure: 0.7461, kappa: 0.4922, kb_relative_information_score: 348.2872, mean_absolute_error: 0.3453, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7462, predictive_accuracy: 0.7461, prior_entropy: 1, recall: 0.7461, relative_absolute_error: 0.6905, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4195, root_relative_squared_error: 0.839, scimark_benchmark: 824.2652,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8122, build_cpu_time: 7.5581, build_memory: 1057060860.6563, f_measure: 0.7441, kappa: 0.4882, kb_relative_information_score: 347.352, mean_absolute_error: 0.3459, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7442, predictive_accuracy: 0.7441, prior_entropy: 1, recall: 0.7441, relative_absolute_error: 0.6918, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4187, root_relative_squared_error: 0.8374, scimark_benchmark: 946.197,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8118, build_cpu_time: 14.2918, build_memory: 896776929.7109, f_measure: 0.748, kappa: 0.4961, kb_relative_information_score: 344.5276, mean_absolute_error: 0.3472, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7481, predictive_accuracy: 0.748, prior_entropy: 1, recall: 0.748, relative_absolute_error: 0.6944, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4189, root_relative_squared_error: 0.8378, scimark_benchmark: 944.5105,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8109, build_cpu_time: 30.015, build_memory: 419640866.3281, f_measure: 0.7451, kappa: 0.4902, kb_relative_information_score: 343.9784, mean_absolute_error: 0.3474, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7451, predictive_accuracy: 0.7451, prior_entropy: 1, recall: 0.7451, relative_absolute_error: 0.6949, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4193, root_relative_squared_error: 0.8385, scimark_benchmark: 931.9798,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8122, build_cpu_time: 1.1628, build_memory: 241814551.7031, f_measure: 0.7352, kappa: 0.4705, kb_relative_information_score: 467.9022, mean_absolute_error: 0.2728, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7358, predictive_accuracy: 0.7354, prior_entropy: 1, recall: 0.7354, relative_absolute_error: 0.5455, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4693, root_relative_squared_error: 0.9386, scimark_benchmark: 934.1739,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8136, build_cpu_time: 0.3045, build_memory: 127279149.7266, f_measure: 0.7359, kappa: 0.4724, kb_relative_information_score: 467.3335, mean_absolute_error: 0.2738, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7375, predictive_accuracy: 0.7363, prior_entropy: 1, recall: 0.7363, relative_absolute_error: 0.5477, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4686, root_relative_squared_error: 0.9372, scimark_benchmark: 941.4198,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.814, build_cpu_time: 0.2161, build_memory: 1641013298.5469, f_measure: 0.7429, kappa: 0.4861, kb_relative_information_score: 465.0393, mean_absolute_error: 0.2759, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7439, predictive_accuracy: 0.7432, prior_entropy: 1, recall: 0.7432, relative_absolute_error: 0.5518, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4602, root_relative_squared_error: 0.9205, scimark_benchmark: 920.6195,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8019, build_cpu_time: 1.4002, build_memory: 1640270746.2969, f_measure: 0.7183, kappa: 0.4372, kb_relative_information_score: 289.5291, mean_absolute_error: 0.3776, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7197, predictive_accuracy: 0.7188, prior_entropy: 1, recall: 0.7188, relative_absolute_error: 0.7551, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4276, root_relative_squared_error: 0.8552, scimark_benchmark: 944.9998,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8016, build_cpu_time: 2.9189, build_memory: 824736565.4609, f_measure: 0.7192, kappa: 0.4392, kb_relative_information_score: 288.7834, mean_absolute_error: 0.3778, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7212, predictive_accuracy: 0.7197, prior_entropy: 1, recall: 0.7197, relative_absolute_error: 0.7556, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4283, root_relative_squared_error: 0.8567, scimark_benchmark: 944.4278,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8008, build_cpu_time: 0.3886, build_memory: 812364996.5078, f_measure: 0.7334, kappa: 0.4668, kb_relative_information_score: 324.9937, mean_absolute_error: 0.359, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7334, predictive_accuracy: 0.7334, prior_entropy: 1, recall: 0.7334, relative_absolute_error: 0.718, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4245, root_relative_squared_error: 0.849, scimark_benchmark: 940.6705,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8006, build_cpu_time: 0.1998, build_memory: 134387608.2266, f_measure: 0.7305, kappa: 0.4609, kb_relative_information_score: 324.4623, mean_absolute_error: 0.3592, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7305, predictive_accuracy: 0.7305, prior_entropy: 1, recall: 0.7305, relative_absolute_error: 0.7184, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4247, root_relative_squared_error: 0.8495, scimark_benchmark: 930.2373,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8022, build_cpu_time: 0.0914, build_memory: 1056630138.7734, f_measure: 0.7324, kappa: 0.4648, kb_relative_information_score: 326.1689, mean_absolute_error: 0.3583, mean_prior_absolute_error: 0.5, number_of_instances: 1024, precision: 0.7324, predictive_accuracy: 0.7324, prior_entropy: 1, recall: 0.7324, relative_absolute_error: 0.7167, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4251, root_relative_squared_error: 0.8502, scimark_benchmark: 943.1158,

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