OpenML
Supervised Classification on cloud

Supervised Classification on cloud

Task 3753 Supervised Classification cloud 854 runs submitted
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  • study_1 study_107 study_123 study_41 study_7 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9137, build_cpu_time: 0.021, build_memory: 1736817756.8148, f_measure: 0.7513, kappa: 0.3769, kb_relative_information_score: 32.3145, mean_absolute_error: 0.3014, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.7729, predictive_accuracy: 0.7778, prior_entropy: 0.8813, recall: 0.7778, relative_absolute_error: 0.7202, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3626, root_relative_squared_error: 0.794, scimark_benchmark: 943.4766,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9075, build_cpu_time: 0.0104, build_memory: 1549968535.7037, f_measure: 0.7513, kappa: 0.3769, kb_relative_information_score: 32.8852, mean_absolute_error: 0.298, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.7729, predictive_accuracy: 0.7778, prior_entropy: 0.8813, recall: 0.7778, relative_absolute_error: 0.7122, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3645, root_relative_squared_error: 0.7982, scimark_benchmark: 941.5201,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7469, build_cpu_time: 0.0164, build_memory: 2703429165.3333, f_measure: 0.7127, kappa: 0.2849, kb_relative_information_score: 17.3503, mean_absolute_error: 0.3442, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.7112, predictive_accuracy: 0.7315, prior_entropy: 0.8813, recall: 0.7315, relative_absolute_error: 0.8225, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.4148, root_relative_squared_error: 0.9083, scimark_benchmark: 941.0866,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7469, build_cpu_time: 0.0165, build_memory: 1265903508.4444, f_measure: 0.7127, kappa: 0.2849, kb_relative_information_score: 17.3503, mean_absolute_error: 0.3442, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.7112, predictive_accuracy: 0.7315, prior_entropy: 0.8813, recall: 0.7315, relative_absolute_error: 0.8225, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.4148, root_relative_squared_error: 0.9083, scimark_benchmark: 946.5543,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6817, build_cpu_time: 2.8307, build_memory: 945288298.4444, f_measure: 0.6822, kappa: 0.2051, kb_relative_information_score: 8.2332, mean_absolute_error: 0.3787, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.7109, predictive_accuracy: 0.7315, prior_entropy: 0.8813, recall: 0.7315, relative_absolute_error: 0.9049, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.4331, root_relative_squared_error: 0.9484, scimark_benchmark: 939.5765,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6587, build_cpu_time: 0.1877, build_memory: 905734082.3704, f_measure: 0.6752, kappa: 0.1867, kb_relative_information_score: 7.8086, mean_absolute_error: 0.3793, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.6933, predictive_accuracy: 0.7222, prior_entropy: 0.8813, recall: 0.7222, relative_absolute_error: 0.9062, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.437, root_relative_squared_error: 0.9571, scimark_benchmark: 941.6532,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6587, build_cpu_time: 0.2398, build_memory: 2280856831.3333, f_measure: 0.6752, kappa: 0.1867, kb_relative_information_score: 7.8086, mean_absolute_error: 0.3793, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.6933, predictive_accuracy: 0.7222, prior_entropy: 0.8813, recall: 0.7222, relative_absolute_error: 0.9062, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.437, root_relative_squared_error: 0.9571, scimark_benchmark: 940.6012,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9003, build_cpu_time: 0.002, build_memory: 522142012.7407, f_measure: 0.8364, kappa: 0.597, kb_relative_information_score: 62.453, mean_absolute_error: 0.1667, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.839, predictive_accuracy: 0.8426, prior_entropy: 0.8813, recall: 0.8426, relative_absolute_error: 0.3982, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3367, root_relative_squared_error: 0.7372, scimark_benchmark: 926.9727,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9377, build_cpu_time: 0.0034, build_memory: 534257512.5926, f_measure: 0.8341, kappa: 0.5891, kb_relative_information_score: 62.7519, mean_absolute_error: 0.1667, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8408, predictive_accuracy: 0.8426, prior_entropy: 0.8813, recall: 0.8426, relative_absolute_error: 0.3982, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3295, root_relative_squared_error: 0.7216, scimark_benchmark: 938.3567,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9383, build_cpu_time: 0.0103, build_memory: 169051694.8148, f_measure: 0.8256, kappa: 0.5691, kb_relative_information_score: 62.4346, mean_absolute_error: 0.1694, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8294, predictive_accuracy: 0.8333, prior_entropy: 0.8813, recall: 0.8333, relative_absolute_error: 0.4049, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3222, root_relative_squared_error: 0.7057, scimark_benchmark: 932.7461,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9383, build_cpu_time: 0.037, build_memory: 561189660.2963, f_measure: 0.8256, kappa: 0.5691, kb_relative_information_score: 62.4346, mean_absolute_error: 0.1694, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8294, predictive_accuracy: 0.8333, prior_entropy: 0.8813, recall: 0.8333, relative_absolute_error: 0.4049, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3222, root_relative_squared_error: 0.7057, scimark_benchmark: 940.6012,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9383, build_cpu_time: 0.0067, build_memory: 982841161.3333, f_measure: 0.8256, kappa: 0.5691, kb_relative_information_score: 62.4346, mean_absolute_error: 0.1694, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8294, predictive_accuracy: 0.8333, prior_entropy: 0.8813, recall: 0.8333, relative_absolute_error: 0.4049, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3222, root_relative_squared_error: 0.7057, scimark_benchmark: 938.3567,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9461, build_cpu_time: 0.0156, build_memory: 552111878.2963, f_measure: 0.8341, kappa: 0.5891, kb_relative_information_score: 63.1189, mean_absolute_error: 0.1663, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8408, predictive_accuracy: 0.8426, prior_entropy: 0.8813, recall: 0.8426, relative_absolute_error: 0.3974, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3149, root_relative_squared_error: 0.6896, scimark_benchmark: 785.9104,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9461, build_cpu_time: 0.0342, build_memory: 669225393.7778, f_measure: 0.8341, kappa: 0.5891, kb_relative_information_score: 63.1189, mean_absolute_error: 0.1663, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8408, predictive_accuracy: 0.8426, prior_entropy: 0.8813, recall: 0.8426, relative_absolute_error: 0.3974, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3149, root_relative_squared_error: 0.6896, scimark_benchmark: 940.6012,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6552, build_cpu_time: 0.0451, build_memory: 910215193.6296, f_measure: 0.5813, kb_relative_information_score: 1.4688, mean_absolute_error: 0.4109, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.4952, predictive_accuracy: 0.7037, prior_entropy: 0.8813, recall: 0.7037, relative_absolute_error: 0.9818, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.4504, root_relative_squared_error: 0.9863, scimark_benchmark: 938.3567,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9439, build_cpu_time: 0.0385, build_memory: 97622297.4074, f_measure: 0.8341, kappa: 0.5891, kb_relative_information_score: 62.3943, mean_absolute_error: 0.1688, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8408, predictive_accuracy: 0.8426, prior_entropy: 0.8813, recall: 0.8426, relative_absolute_error: 0.4032, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3171, root_relative_squared_error: 0.6944, scimark_benchmark: 934.625,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9439, build_cpu_time: 0.035, build_memory: 166485994.5926, f_measure: 0.8341, kappa: 0.5891, kb_relative_information_score: 62.3943, mean_absolute_error: 0.1688, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8408, predictive_accuracy: 0.8426, prior_entropy: 0.8813, recall: 0.8426, relative_absolute_error: 0.4032, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3171, root_relative_squared_error: 0.6944, scimark_benchmark: 926.9727,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4285, build_cpu_time: 0.0281, build_memory: 805844134, f_measure: 0.5782, kappa: -0.0534, kb_relative_information_score: -16.198, mean_absolute_error: 0.4516, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.5475, predictive_accuracy: 0.6481, prior_entropy: 0.8813, recall: 0.6481, relative_absolute_error: 1.0791, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.4901, root_relative_squared_error: 1.0733, scimark_benchmark: 932.5791,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7422, build_cpu_time: 0.0101, build_memory: 188312299.4074, f_measure: 0.7247, kappa: 0.3165, kb_relative_information_score: 37.0786, mean_absolute_error: 0.2537, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.7233, predictive_accuracy: 0.7407, prior_entropy: 0.8813, recall: 0.7407, relative_absolute_error: 0.6062, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.4881, root_relative_squared_error: 1.0689, scimark_benchmark: 941.5045,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4063, build_cpu_time: 8.7124, build_memory: 250718944.8889, f_measure: 0.5979, kappa: -0.0079, kb_relative_information_score: -10.9475, mean_absolute_error: 0.4381, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.5787, predictive_accuracy: 0.6481, prior_entropy: 0.8813, recall: 0.6481, relative_absolute_error: 1.0469, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.5054, root_relative_squared_error: 1.1069, scimark_benchmark: 931.2177,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.403, build_cpu_time: 16.607, build_memory: 282043818.6667, f_measure: 0.5979, kappa: -0.0079, kb_relative_information_score: -11.2358, mean_absolute_error: 0.4404, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.5787, predictive_accuracy: 0.6481, prior_entropy: 0.8813, recall: 0.6481, relative_absolute_error: 1.0522, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.505, root_relative_squared_error: 1.1058, scimark_benchmark: 945.6653,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5617, build_cpu_time: 0.0184, build_memory: 891511441.2593, f_measure: 0.7107, kappa: 0.2827, kb_relative_information_score: 11.2824, mean_absolute_error: 0.3757, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8258, predictive_accuracy: 0.7685, prior_entropy: 0.8813, recall: 0.7685, relative_absolute_error: 0.8977, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.431, root_relative_squared_error: 0.9439, scimark_benchmark: 942.4935,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5929, build_cpu_time: 0.002, build_memory: 871468736.963, f_measure: 0.7263, kappa: 0.3193, kb_relative_information_score: 14.0091, mean_absolute_error: 0.3649, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8311, predictive_accuracy: 0.7778, prior_entropy: 0.8813, recall: 0.7778, relative_absolute_error: 0.8719, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.4257, root_relative_squared_error: 0.9322, scimark_benchmark: 1212.2248,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5831, build_cpu_time: 0.0016, build_memory: 1098373675.5556, f_measure: 0.7188, kappa: 0.2991, kb_relative_information_score: 13.9821, mean_absolute_error: 0.3653, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.7965, predictive_accuracy: 0.7685, prior_entropy: 0.8813, recall: 0.7685, relative_absolute_error: 0.8728, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.4297, root_relative_squared_error: 0.941, scimark_benchmark: 941.5509,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8289, build_cpu_time: 0.3208, build_memory: 1211763422.4444, f_measure: 0.7756, kappa: 0.444, kb_relative_information_score: 32.957, mean_absolute_error: 0.2915, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.7774, predictive_accuracy: 0.787, prior_entropy: 0.8813, recall: 0.787, relative_absolute_error: 0.6965, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3806, root_relative_squared_error: 0.8334, scimark_benchmark: 821.7292,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8475, build_cpu_time: 0.7222, build_memory: 847028602.0741, f_measure: 0.7444, kappa: 0.3653, kb_relative_information_score: 32.9885, mean_absolute_error: 0.2918, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.745, predictive_accuracy: 0.7593, prior_entropy: 0.8813, recall: 0.7593, relative_absolute_error: 0.6972, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3775, root_relative_squared_error: 0.8266, scimark_benchmark: 942.9616,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.869, build_cpu_time: 0.2942, build_memory: 1139034552.2222, f_measure: 0.817, kappa: 0.5424, kb_relative_information_score: 45.2093, mean_absolute_error: 0.2478, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.842, predictive_accuracy: 0.8333, prior_entropy: 0.8813, recall: 0.8333, relative_absolute_error: 0.592, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3613, root_relative_squared_error: 0.7913, scimark_benchmark: 784.8833,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8697, build_cpu_time: 0.3753, build_memory: 1981616122.5185, f_measure: 0.817, kappa: 0.5424, kb_relative_information_score: 44.3252, mean_absolute_error: 0.2518, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.842, predictive_accuracy: 0.8333, prior_entropy: 0.8813, recall: 0.8333, relative_absolute_error: 0.6015, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3627, root_relative_squared_error: 0.7944, scimark_benchmark: 931.6165,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8746, build_cpu_time: 0.1321, build_memory: 319302361.037, f_measure: 0.7951, kappa: 0.4924, kb_relative_information_score: 41.9463, mean_absolute_error: 0.2663, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.7985, predictive_accuracy: 0.8056, prior_entropy: 0.8813, recall: 0.8056, relative_absolute_error: 0.6363, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3563, root_relative_squared_error: 0.7803, scimark_benchmark: 806.1692,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8832, build_cpu_time: 0.0731, build_memory: 1348608199.7778, f_measure: 0.8062, kappa: 0.5213, kb_relative_information_score: 43.3091, mean_absolute_error: 0.262, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8086, predictive_accuracy: 0.8148, prior_entropy: 0.8813, recall: 0.8148, relative_absolute_error: 0.6261, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3522, root_relative_squared_error: 0.7712, scimark_benchmark: 941.6518,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.889, build_cpu_time: 0.0455, build_memory: 2458486577.4815, f_measure: 0.7951, kappa: 0.4924, kb_relative_information_score: 44.3581, mean_absolute_error: 0.2533, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.7985, predictive_accuracy: 0.8056, prior_entropy: 0.8813, recall: 0.8056, relative_absolute_error: 0.6053, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3529, root_relative_squared_error: 0.7729, scimark_benchmark: 942.6685,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8594, build_cpu_time: 0.0146, build_memory: 1559700097.1852, f_measure: 0.7868, kappa: 0.4734, kb_relative_information_score: 41.6914, mean_absolute_error: 0.2604, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.7879, predictive_accuracy: 0.7963, prior_entropy: 0.8813, recall: 0.7963, relative_absolute_error: 0.6223, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3682, root_relative_squared_error: 0.8064, scimark_benchmark: 939.3558,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8594, build_cpu_time: 0.0127, build_memory: 1414779863.1111, f_measure: 0.7868, kappa: 0.4734, kb_relative_information_score: 41.6914, mean_absolute_error: 0.2604, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.7879, predictive_accuracy: 0.7963, prior_entropy: 0.8813, recall: 0.7963, relative_absolute_error: 0.6223, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3682, root_relative_squared_error: 0.8064, scimark_benchmark: 946.5777,

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