Task
Supervised Classification on analcatdata_gsssexsurvey

Supervised Classification on analcatdata_gsssexsurvey

Task 4422 Supervised Classification analcatdata_gsssexsurvey 214 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5098, f_measure: 0.7217, kappa: 0.1135, kb_relative_information_score: 77.0992, mean_absolute_error: 0.3277, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.7358, predictive_accuracy: 0.7824, prior_entropy: 0.7667, recall: 0.7824, relative_absolute_error: 0.949, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4103, root_relative_squared_error: 0.9903, scimark_benchmark: 906.0979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5784, f_measure: 0.6815, kappa: -0.0064, kb_relative_information_score: -396.9613, mean_absolute_error: 0.3677, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.6537, predictive_accuracy: 0.7296, prior_entropy: 0.7667, recall: 0.7296, relative_absolute_error: 1.0648, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4371, root_relative_squared_error: 1.0548, scimark_benchmark: 972.587,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6075, f_measure: 0.6856, kappa: 0.027, kb_relative_information_score: -157.3325, mean_absolute_error: 0.3303, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.6668, predictive_accuracy: 0.7132, prior_entropy: 0.7667, recall: 0.7132, relative_absolute_error: 0.9566, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4534, root_relative_squared_error: 1.0941, scimark_benchmark: 934.3687, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4993, f_measure: 0.6842, kappa: -0.0022, kb_relative_information_score: 384.3197, mean_absolute_error: 0.2277, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.652, predictive_accuracy: 0.7723, prior_entropy: 0.7667, recall: 0.7723, relative_absolute_error: 0.6594, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4772, root_relative_squared_error: 1.1516, scimark_benchmark: 931.771, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4993, f_measure: 0.6842, kappa: -0.0022, kb_relative_information_score: 384.3197, mean_absolute_error: 0.2277, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.652, predictive_accuracy: 0.7723, prior_entropy: 0.7667, recall: 0.7723, relative_absolute_error: 0.6594, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4772, root_relative_squared_error: 1.1516, scimark_benchmark: 944.1067, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5939, f_measure: 0.7191, kappa: 0.1071, kb_relative_information_score: 83.954, mean_absolute_error: 0.3148, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.7155, predictive_accuracy: 0.7717, prior_entropy: 0.7667, recall: 0.7717, relative_absolute_error: 0.9117, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4072, root_relative_squared_error: 0.9827, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.586, f_measure: 0.7128, kappa: 0.0857, kb_relative_information_score: 72.3526, mean_absolute_error: 0.3156, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.7092, predictive_accuracy: 0.7711, prior_entropy: 0.7667, recall: 0.7711, relative_absolute_error: 0.9141, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4054, root_relative_squared_error: 0.9783, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.586, f_measure: 0.7128, kappa: 0.0857, kb_relative_information_score: 72.3526, mean_absolute_error: 0.3156, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.7092, predictive_accuracy: 0.7711, prior_entropy: 0.7667, recall: 0.7711, relative_absolute_error: 0.9141, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4054, root_relative_squared_error: 0.9783, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.586, f_measure: 0.7128, kappa: 0.0857, kb_relative_information_score: 72.3526, mean_absolute_error: 0.3156, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.7092, predictive_accuracy: 0.7711, prior_entropy: 0.7667, recall: 0.7711, relative_absolute_error: 0.9141, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4054, root_relative_squared_error: 0.9783, scimark_benchmark: 938.191,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5692, f_measure: 0.6847, kappa: -0.0031, kb_relative_information_score: -89.9161, mean_absolute_error: 0.3358, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.6531, predictive_accuracy: 0.7654, prior_entropy: 0.7667, recall: 0.7654, relative_absolute_error: 0.9724, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4199, root_relative_squared_error: 1.0134, scimark_benchmark: 938.191, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5643, f_measure: 0.7025, kappa: 0.0541, kb_relative_information_score: 15.5873, mean_absolute_error: 0.3217, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.6866, predictive_accuracy: 0.7585, prior_entropy: 0.7667, recall: 0.7585, relative_absolute_error: 0.9318, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4184, root_relative_squared_error: 1.0099, scimark_benchmark: 905.2959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4993, f_measure: 0.6842, kappa: -0.0022, kb_relative_information_score: 384.3197, mean_absolute_error: 0.2277, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.652, predictive_accuracy: 0.7723, prior_entropy: 0.7667, recall: 0.7723, relative_absolute_error: 0.6594, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4772, root_relative_squared_error: 1.1516, scimark_benchmark: 937.5117, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4993, f_measure: 0.6842, kappa: -0.0022, kb_relative_information_score: 384.3197, mean_absolute_error: 0.2277, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.652, predictive_accuracy: 0.7723, prior_entropy: 0.7667, recall: 0.7723, relative_absolute_error: 0.6594, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4772, root_relative_squared_error: 1.1516, scimark_benchmark: 974.2014, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5939, f_measure: 0.7191, kappa: 0.1071, kb_relative_information_score: 83.954, mean_absolute_error: 0.3148, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.7155, predictive_accuracy: 0.7717, prior_entropy: 0.7667, recall: 0.7717, relative_absolute_error: 0.9117, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4072, root_relative_squared_error: 0.9827, scimark_benchmark: 932.438,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.586, f_measure: 0.7128, kappa: 0.0857, kb_relative_information_score: 72.3526, mean_absolute_error: 0.3156, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.7092, predictive_accuracy: 0.7711, prior_entropy: 0.7667, recall: 0.7711, relative_absolute_error: 0.9141, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4054, root_relative_squared_error: 0.9783, scimark_benchmark: 947.1781, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5538, f_measure: 0.6895, kappa: 0.0311, kb_relative_information_score: -213.403, mean_absolute_error: 0.3417, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.6689, predictive_accuracy: 0.7233, prior_entropy: 0.7667, recall: 0.7233, relative_absolute_error: 0.9896, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4442, root_relative_squared_error: 1.072, scimark_benchmark: 974.2014, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5098, f_measure: 0.7217, kappa: 0.1135, kb_relative_information_score: 77.0992, mean_absolute_error: 0.3277, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.7358, predictive_accuracy: 0.7824, prior_entropy: 0.7667, recall: 0.7824, relative_absolute_error: 0.949, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4103, root_relative_squared_error: 0.9903, scimark_benchmark: 942.2392,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5784, f_measure: 0.6815, kappa: -0.0064, kb_relative_information_score: -396.9613, mean_absolute_error: 0.3677, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.6537, predictive_accuracy: 0.7296, prior_entropy: 0.7667, recall: 0.7296, relative_absolute_error: 1.0648, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4371, root_relative_squared_error: 1.0548, scimark_benchmark: 908.9569,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6075, f_measure: 0.6856, kappa: 0.027, kb_relative_information_score: -157.3325, mean_absolute_error: 0.3303, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.6668, predictive_accuracy: 0.7132, prior_entropy: 0.7667, recall: 0.7132, relative_absolute_error: 0.9566, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4534, root_relative_squared_error: 1.0941, scimark_benchmark: 936.2574, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4993, f_measure: 0.6842, kappa: -0.0022, kb_relative_information_score: 384.3197, mean_absolute_error: 0.2277, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.652, predictive_accuracy: 0.7723, prior_entropy: 0.7667, recall: 0.7723, relative_absolute_error: 0.6594, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4772, root_relative_squared_error: 1.1516, scimark_benchmark: 926.5462, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.586, f_measure: 0.7128, kappa: 0.0857, kb_relative_information_score: 72.3526, mean_absolute_error: 0.3156, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.7092, predictive_accuracy: 0.7711, prior_entropy: 0.7667, recall: 0.7711, relative_absolute_error: 0.9141, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4054, root_relative_squared_error: 0.9783, scimark_benchmark: 930.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.586, f_measure: 0.7128, kappa: 0.0857, kb_relative_information_score: 72.3526, mean_absolute_error: 0.3156, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.7092, predictive_accuracy: 0.7711, prior_entropy: 0.7667, recall: 0.7711, relative_absolute_error: 0.9141, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4054, root_relative_squared_error: 0.9783, scimark_benchmark: 941.4991,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5692, f_measure: 0.6847, kappa: -0.0031, kb_relative_information_score: -89.9161, mean_absolute_error: 0.3358, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.6531, predictive_accuracy: 0.7654, prior_entropy: 0.7667, recall: 0.7654, relative_absolute_error: 0.9724, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4199, root_relative_squared_error: 1.0134, scimark_benchmark: 903.2737,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.598, f_measure: 0.7147, kappa: 0.0921, kb_relative_information_score: -17.4004, mean_absolute_error: 0.3207, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.7118, predictive_accuracy: 0.7717, prior_entropy: 0.7667, recall: 0.7717, relative_absolute_error: 0.9289, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4136, root_relative_squared_error: 0.9981, scimark_benchmark: 919.3788, usercpu_time_millis: 150, usercpu_time_millis_training: 150,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.586, f_measure: 0.7128, kappa: 0.0857, kb_relative_information_score: 72.3526, mean_absolute_error: 0.3156, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.7092, predictive_accuracy: 0.7711, prior_entropy: 0.7667, recall: 0.7711, relative_absolute_error: 0.9141, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4054, root_relative_squared_error: 0.9783, scimark_benchmark: 944.0133, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5643, f_measure: 0.7025, kappa: 0.0541, kb_relative_information_score: 15.5873, mean_absolute_error: 0.3217, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.6866, predictive_accuracy: 0.7585, prior_entropy: 0.7667, recall: 0.7585, relative_absolute_error: 0.9318, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4184, root_relative_squared_error: 1.0099, scimark_benchmark: 730.6551, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5538, f_measure: 0.6895, kappa: 0.0311, kb_relative_information_score: -213.403, mean_absolute_error: 0.3417, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.6689, predictive_accuracy: 0.7233, prior_entropy: 0.7667, recall: 0.7233, relative_absolute_error: 0.9896, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4442, root_relative_squared_error: 1.072, scimark_benchmark: 936.9595, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5602, f_measure: 0.7004, kappa: 0.0474, kb_relative_information_score: -21.7986, mean_absolute_error: 0.3358, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.7193, predictive_accuracy: 0.7792, prior_entropy: 0.7667, recall: 0.7792, relative_absolute_error: 0.9724, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4131, root_relative_squared_error: 0.997, scimark_benchmark: 935.5664, usercpu_time_millis: 660, usercpu_time_millis_testing: 300, usercpu_time_millis_training: 360,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5637, f_measure: 0.7087, kappa: 0.0735, kb_relative_information_score: -16.5445, mean_absolute_error: 0.3349, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.7425, predictive_accuracy: 0.7836, prior_entropy: 0.7667, recall: 0.7836, relative_absolute_error: 0.9699, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4121, root_relative_squared_error: 0.9946, scimark_benchmark: 906.5979, usercpu_time_millis: 520, usercpu_time_millis_testing: 320, usercpu_time_millis_training: 200,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5552, f_measure: 0.6983, kappa: 0.0407, kb_relative_information_score: -20.0647, mean_absolute_error: 0.3356, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.7091, predictive_accuracy: 0.7774, prior_entropy: 0.7667, recall: 0.7774, relative_absolute_error: 0.9718, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4137, root_relative_squared_error: 0.9984, scimark_benchmark: 921.466, usercpu_time_millis: 140, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 100,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5482, f_measure: 0.6953, kappa: 0.0311, kb_relative_information_score: -27.3312, mean_absolute_error: 0.3358, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.6978, predictive_accuracy: 0.7755, prior_entropy: 0.7667, recall: 0.7755, relative_absolute_error: 0.9725, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4145, root_relative_squared_error: 1.0003, scimark_benchmark: 944.235, usercpu_time_millis: 70, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5415, f_measure: 0.7061, kappa: 0.0645, kb_relative_information_score: -38.2774, mean_absolute_error: 0.3371, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.7219, predictive_accuracy: 0.7792, prior_entropy: 0.7667, recall: 0.7792, relative_absolute_error: 0.9763, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4169, root_relative_squared_error: 1.0062, scimark_benchmark: 920.3788, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5891, f_measure: 0.7079, kappa: 0.0808, kb_relative_information_score: -27.1152, mean_absolute_error: 0.3159, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.6912, predictive_accuracy: 0.7472, prior_entropy: 0.7667, recall: 0.7472, relative_absolute_error: 0.9149, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4375, root_relative_squared_error: 1.0558, scimark_benchmark: 929.0296,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5891, f_measure: 0.7079, kappa: 0.0808, kb_relative_information_score: -27.1152, mean_absolute_error: 0.3159, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.6912, predictive_accuracy: 0.7472, prior_entropy: 0.7667, recall: 0.7472, relative_absolute_error: 0.9149, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4375, root_relative_squared_error: 1.0558, scimark_benchmark: 941.9549,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5891, f_measure: 0.7079, kappa: 0.0808, kb_relative_information_score: -27.1152, mean_absolute_error: 0.3159, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.6912, predictive_accuracy: 0.7472, prior_entropy: 0.7667, recall: 0.7472, relative_absolute_error: 0.9149, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4375, root_relative_squared_error: 1.0558, scimark_benchmark: 894.7131, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5891, f_measure: 0.7079, kappa: 0.0808, kb_relative_information_score: -27.3437, mean_absolute_error: 0.316, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.6912, predictive_accuracy: 0.7472, prior_entropy: 0.7667, recall: 0.7472, relative_absolute_error: 0.9151, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4375, root_relative_squared_error: 1.0558, scimark_benchmark: 941.9549,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5975, f_measure: 0.7062, kappa: 0.0749, kb_relative_information_score: -28.1881, mean_absolute_error: 0.3174, mean_prior_absolute_error: 0.3453, number_of_instances: 1590, precision: 0.689, predictive_accuracy: 0.7465, prior_entropy: 0.7667, recall: 0.7465, relative_absolute_error: 0.9193, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4343, root_relative_squared_error: 1.0482, scimark_benchmark: 926.5859, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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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