OpenML
Supervised Classification on analcatdata_supreme

Supervised Classification on analcatdata_supreme

Task 3594 Supervised Classification analcatdata_supreme 539 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: 0.9859, build_cpu_time: 0.0988, build_memory: 668583594.6851, f_measure: 0.9931, kappa: 0.9809, kb_relative_information_score: 3964.3776, mean_absolute_error: 0.0069, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9931, predictive_accuracy: 0.9931, prior_entropy: 0.7946, recall: 0.9931, relative_absolute_error: 0.019, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0831, root_relative_squared_error: 0.1947, scimark_benchmark: 938.3567,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9859, build_cpu_time: 0.1256, build_memory: 441136787.3425, f_measure: 0.9931, kappa: 0.9809, kb_relative_information_score: 3964.3776, mean_absolute_error: 0.0069, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9931, predictive_accuracy: 0.9931, prior_entropy: 0.7946, recall: 0.9931, relative_absolute_error: 0.019, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0831, root_relative_squared_error: 0.1947, scimark_benchmark: 938.3567,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9859, build_cpu_time: 0.1259, build_memory: 768682980.5094, f_measure: 0.9931, kappa: 0.9809, kb_relative_information_score: 3964.3776, mean_absolute_error: 0.0069, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9931, predictive_accuracy: 0.9931, prior_entropy: 0.7946, recall: 0.9931, relative_absolute_error: 0.019, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0831, root_relative_squared_error: 0.1947, scimark_benchmark: 937.52,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9994, build_cpu_time: 2.5709, build_memory: 391837566.1619, f_measure: 0.9928, kappa: 0.9802, kb_relative_information_score: 3919.7791, mean_absolute_error: 0.0123, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9929, predictive_accuracy: 0.9928, prior_entropy: 0.7946, recall: 0.9928, relative_absolute_error: 0.0339, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0752, root_relative_squared_error: 0.1762, scimark_benchmark: 899.912,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9981, build_cpu_time: 0.6219, build_memory: 249849742.1639, f_measure: 0.9923, kappa: 0.9789, kb_relative_information_score: 3918.231, mean_absolute_error: 0.0124, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9924, predictive_accuracy: 0.9923, prior_entropy: 0.7946, recall: 0.9923, relative_absolute_error: 0.034, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0763, root_relative_squared_error: 0.1788, scimark_benchmark: 902.1764,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9871, build_cpu_time: 0.6449, build_memory: 1020243786.5193, f_measure: 0.9742, kappa: 0.9296, kb_relative_information_score: 3196.1677, mean_absolute_error: 0.0832, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9745, predictive_accuracy: 0.9741, prior_entropy: 0.7946, recall: 0.9741, relative_absolute_error: 0.2283, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.1758, root_relative_squared_error: 0.4118, scimark_benchmark: 932.5791,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9907, build_cpu_time: 0.1704, build_memory: 73466244.7206, f_measure: 0.9857, kappa: 0.9609, kb_relative_information_score: 3495.5038, mean_absolute_error: 0.0537, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9858, predictive_accuracy: 0.9857, prior_entropy: 0.7946, recall: 0.9857, relative_absolute_error: 0.1472, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.1501, root_relative_squared_error: 0.3518, scimark_benchmark: 926.5157,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9849, build_cpu_time: 0.076, build_memory: 323725571.7236, f_measure: 0.974, kappa: 0.929, kb_relative_information_score: 3194.0366, mean_absolute_error: 0.0833, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9743, predictive_accuracy: 0.9738, prior_entropy: 0.7946, recall: 0.9738, relative_absolute_error: 0.2286, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.178, root_relative_squared_error: 0.4171, scimark_benchmark: 939.2194,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9849, build_cpu_time: 0.0763, build_memory: 174438835.2952, f_measure: 0.974, kappa: 0.929, kb_relative_information_score: 3194.0366, mean_absolute_error: 0.0833, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9743, predictive_accuracy: 0.9738, prior_entropy: 0.7946, recall: 0.9738, relative_absolute_error: 0.2286, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.178, root_relative_squared_error: 0.4171, scimark_benchmark: 929.8459,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9945, build_cpu_time: 266.65, build_memory: 882215187.3327, f_measure: 0.9926, kappa: 0.9795, kb_relative_information_score: 3930.8275, mean_absolute_error: 0.0107, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9926, predictive_accuracy: 0.9926, prior_entropy: 0.7946, recall: 0.9926, relative_absolute_error: 0.0294, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0841, root_relative_squared_error: 0.1971, scimark_benchmark: 915.2996,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9941, build_cpu_time: 542.668, build_memory: 1095746018.2665, f_measure: 0.9926, kappa: 0.9795, kb_relative_information_score: 3931.0452, mean_absolute_error: 0.0107, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9926, predictive_accuracy: 0.9926, prior_entropy: 0.7946, recall: 0.9926, relative_absolute_error: 0.0293, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0843, root_relative_squared_error: 0.1976, scimark_benchmark: 941.326,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9934, build_cpu_time: 0.1494, build_memory: 919557128.7502, f_measure: 0.9931, kappa: 0.9809, kb_relative_information_score: 3914.507, mean_absolute_error: 0.0137, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9931, predictive_accuracy: 0.9931, prior_entropy: 0.7946, recall: 0.9931, relative_absolute_error: 0.0375, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0827, root_relative_squared_error: 0.1937, scimark_benchmark: 942.9616,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9974, build_cpu_time: 2.4758, build_memory: 962132624.8134, f_measure: 0.9894, kappa: 0.9708, kb_relative_information_score: 3851.5643, mean_absolute_error: 0.0187, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9894, predictive_accuracy: 0.9894, prior_entropy: 0.7946, recall: 0.9894, relative_absolute_error: 0.0513, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.1015, root_relative_squared_error: 0.2377, scimark_benchmark: 943.0515,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9934, build_cpu_time: 0.0557, build_memory: 712992894.7108, f_measure: 0.9931, kappa: 0.9809, kb_relative_information_score: 3914.0688, mean_absolute_error: 0.0137, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9931, predictive_accuracy: 0.9931, prior_entropy: 0.7946, recall: 0.9931, relative_absolute_error: 0.0376, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0827, root_relative_squared_error: 0.1937, scimark_benchmark: 949.7836,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9935, build_cpu_time: 0.0435, build_memory: 217765498.3179, f_measure: 0.9931, kappa: 0.9809, kb_relative_information_score: 3914.1489, mean_absolute_error: 0.0137, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9931, predictive_accuracy: 0.9931, prior_entropy: 0.7946, recall: 0.9931, relative_absolute_error: 0.0376, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0827, root_relative_squared_error: 0.1937, scimark_benchmark: 1223.0194,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9925, build_cpu_time: 4.0317, build_memory: 1472033499.925, f_measure: 0.9904, kappa: 0.9735, kb_relative_information_score: 3930.3452, mean_absolute_error: 0.0097, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9904, predictive_accuracy: 0.9904, prior_entropy: 0.7946, recall: 0.9904, relative_absolute_error: 0.0265, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0965, root_relative_squared_error: 0.226, scimark_benchmark: 942.7079,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9931, build_cpu_time: 0.0117, build_memory: 282706166.4008, f_measure: 0.9931, kappa: 0.9809, kb_relative_information_score: 3913.273, mean_absolute_error: 0.0138, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9931, predictive_accuracy: 0.9931, prior_entropy: 0.7946, recall: 0.9931, relative_absolute_error: 0.0379, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0827, root_relative_squared_error: 0.1937, scimark_benchmark: 824.2652,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9933, build_cpu_time: 2.033, build_memory: 1925426651.1352, f_measure: 0.9911, kappa: 0.9755, kb_relative_information_score: 3939.841, mean_absolute_error: 0.0089, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9911, predictive_accuracy: 0.9911, prior_entropy: 0.7946, recall: 0.9911, relative_absolute_error: 0.0243, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0933, root_relative_squared_error: 0.2186, scimark_benchmark: 942.6348,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9931, build_cpu_time: 0.0088, build_memory: 3474207379.0721, f_measure: 0.9931, kappa: 0.9809, kb_relative_information_score: 3912.8005, mean_absolute_error: 0.0139, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9931, predictive_accuracy: 0.9931, prior_entropy: 0.7946, recall: 0.9931, relative_absolute_error: 0.0381, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0827, root_relative_squared_error: 0.1937, scimark_benchmark: 944.9147,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, build_cpu_time: 9.9933, build_memory: 1568245839.3504, f_measure: 0.9931, kappa: 0.9809, kb_relative_information_score: 3650.2165, mean_absolute_error: 0.0467, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9931, predictive_accuracy: 0.9931, prior_entropy: 0.7946, recall: 0.9931, relative_absolute_error: 0.1281, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0901, root_relative_squared_error: 0.211, scimark_benchmark: 998.3701,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9993, build_cpu_time: 16.1706, build_memory: 745039123.461, f_measure: 0.9923, kappa: 0.9789, kb_relative_information_score: 3668.1339, mean_absolute_error: 0.0452, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9923, predictive_accuracy: 0.9923, prior_entropy: 0.7946, recall: 0.9923, relative_absolute_error: 0.1239, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0864, root_relative_squared_error: 0.2025, scimark_benchmark: 941.6914,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9993, build_cpu_time: 31.8919, build_memory: 127137555.5183, f_measure: 0.9928, kappa: 0.9802, kb_relative_information_score: 3656.5392, mean_absolute_error: 0.0467, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9928, predictive_accuracy: 0.9928, prior_entropy: 0.7946, recall: 0.9928, relative_absolute_error: 0.1281, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.087, root_relative_squared_error: 0.2038, scimark_benchmark: 941.5509,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9993, build_cpu_time: 62.9074, build_memory: 113544602.227, f_measure: 0.9933, kappa: 0.9816, kb_relative_information_score: 3665.8646, mean_absolute_error: 0.0457, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9933, predictive_accuracy: 0.9933, prior_entropy: 0.7946, recall: 0.9933, relative_absolute_error: 0.1254, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0862, root_relative_squared_error: 0.2019, scimark_benchmark: 945.0883,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9935, build_cpu_time: 13.9075, build_memory: 2191238507.8342, f_measure: 0.9923, kappa: 0.9789, kb_relative_information_score: 3955.7888, mean_absolute_error: 0.0075, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9923, predictive_accuracy: 0.9923, prior_entropy: 0.7946, recall: 0.9923, relative_absolute_error: 0.0205, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0848, root_relative_squared_error: 0.1987, scimark_benchmark: 946.2416,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9958, build_cpu_time: 7.1151, build_memory: 889426025.3998, f_measure: 0.9926, kappa: 0.9796, kb_relative_information_score: 3960.7488, mean_absolute_error: 0.0072, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9926, predictive_accuracy: 0.9926, prior_entropy: 0.7946, recall: 0.9926, relative_absolute_error: 0.0197, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0828, root_relative_squared_error: 0.194, scimark_benchmark: 944.0892,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9945, build_cpu_time: 3.877, build_memory: 168289836.7266, f_measure: 0.9921, kappa: 0.9782, kb_relative_information_score: 3954.3015, mean_absolute_error: 0.0077, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9921, predictive_accuracy: 0.9921, prior_entropy: 0.7946, recall: 0.9921, relative_absolute_error: 0.0213, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0853, root_relative_squared_error: 0.1999, scimark_benchmark: 941.4198,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9964, build_cpu_time: 2.1679, build_memory: 562083915.1076, f_measure: 0.9921, kappa: 0.9782, kb_relative_information_score: 3953.7006, mean_absolute_error: 0.0078, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9921, predictive_accuracy: 0.9921, prior_entropy: 0.7946, recall: 0.9921, relative_absolute_error: 0.0214, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0839, root_relative_squared_error: 0.1965, scimark_benchmark: 944.0386,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9964, build_cpu_time: 1.8482, build_memory: 957799583.7058, f_measure: 0.9921, kappa: 0.9782, kb_relative_information_score: 3953.7006, mean_absolute_error: 0.0078, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9921, predictive_accuracy: 0.9921, prior_entropy: 0.7946, recall: 0.9921, relative_absolute_error: 0.0214, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0839, root_relative_squared_error: 0.1965, scimark_benchmark: 931.9798,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9942, build_cpu_time: 3.6132, build_memory: 2367377329.9743, f_measure: 0.9931, kappa: 0.9809, kb_relative_information_score: 3931.4555, mean_absolute_error: 0.0109, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9931, predictive_accuracy: 0.9931, prior_entropy: 0.7946, recall: 0.9931, relative_absolute_error: 0.0299, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0737, root_relative_squared_error: 0.1727, scimark_benchmark: 946.3831,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9959, build_cpu_time: 0.7289, build_memory: 506410724.0138, f_measure: 0.9928, kappa: 0.9802, kb_relative_information_score: 3933.0639, mean_absolute_error: 0.0109, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9929, predictive_accuracy: 0.9928, prior_entropy: 0.7946, recall: 0.9928, relative_absolute_error: 0.0299, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0739, root_relative_squared_error: 0.1732, scimark_benchmark: 942.844,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9961, build_cpu_time: 0.3278, build_memory: 74317889.6269, f_measure: 0.9928, kappa: 0.9802, kb_relative_information_score: 3933.9044, mean_absolute_error: 0.0109, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9929, predictive_accuracy: 0.9928, prior_entropy: 0.7946, recall: 0.9928, relative_absolute_error: 0.0298, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0737, root_relative_squared_error: 0.1727, scimark_benchmark: 944.5208,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9961, build_cpu_time: 0.3464, build_memory: 423383966.3198, f_measure: 0.9928, kappa: 0.9802, kb_relative_information_score: 3933.9044, mean_absolute_error: 0.0109, mean_prior_absolute_error: 0.3645, number_of_instances: 4052, precision: 0.9929, predictive_accuracy: 0.9928, prior_entropy: 0.7946, recall: 0.9928, relative_absolute_error: 0.0298, root_mean_prior_squared_error: 0.4269, root_mean_squared_error: 0.0737, root_relative_squared_error: 0.1727, scimark_benchmark: 937.3599,

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