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OpenML
Task
Supervised Classification on sylva_prior

Supervised Classification on sylva_prior

Task 3893 Supervised Classification sylva_prior 286 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • mythbusting_1 study_1 study_107 study_15 study_20 study_41 under100k
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286 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9939, f_measure: 0.9931, kappa: 0.9413, kb_relative_information_score: 12517.5517, mean_absolute_error: 0.0104, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9933, predictive_accuracy: 0.9931, prior_entropy: 0.3338, recall: 0.9931, relative_absolute_error: 0.0902, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.0811, root_relative_squared_error: 0.3376, scimark_benchmark: 1325.2092, usercpu_time_millis: 100280, usercpu_time_millis_testing: 100280,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9121, f_measure: 0.9823, kappa: 0.8447, kb_relative_information_score: 11280.0602, mean_absolute_error: 0.0175, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9821, predictive_accuracy: 0.9825, prior_entropy: 0.3338, recall: 0.9825, relative_absolute_error: 0.1515, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.1323, root_relative_squared_error: 0.5505, scimark_benchmark: 930.5999, usercpu_time_millis: 7860, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 7820,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9706, f_measure: 0.9934, kappa: 0.9428, kb_relative_information_score: 13214.2877, mean_absolute_error: 0.0066, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9934, predictive_accuracy: 0.9934, prior_entropy: 0.3338, recall: 0.9934, relative_absolute_error: 0.0571, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.0812, root_relative_squared_error: 0.338, scimark_benchmark: 885.0921, usercpu_time_millis: 80960, usercpu_time_millis_testing: 11350, usercpu_time_millis_training: 69610,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9893, f_measure: 0.9949, kappa: 0.9559, kb_relative_information_score: 13460.6861, mean_absolute_error: 0.0052, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.995, predictive_accuracy: 0.9948, prior_entropy: 0.3338, recall: 0.9948, relative_absolute_error: 0.0451, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.0722, root_relative_squared_error: 0.3003, scimark_benchmark: 1333.5799, usercpu_time_millis: 1080, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 1040,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9992, f_measure: 0.9951, kappa: 0.9577, kb_relative_information_score: 13041.8306, mean_absolute_error: 0.0086, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9951, predictive_accuracy: 0.9951, prior_entropy: 0.3338, recall: 0.9951, relative_absolute_error: 0.0748, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.0623, root_relative_squared_error: 0.2594, scimark_benchmark: 887.6719, usercpu_time_millis: 29370, usercpu_time_millis_testing: 90, usercpu_time_millis_training: 29280,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8323, f_measure: 0.9744, kappa: 0.7637, kb_relative_information_score: 10171.2673, mean_absolute_error: 0.0238, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9753, predictive_accuracy: 0.9762, prior_entropy: 0.3338, recall: 0.9762, relative_absolute_error: 0.2056, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.1541, root_relative_squared_error: 0.6413, scimark_benchmark: 1331.6907, usercpu_time_millis: 670, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 640,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.9087, kb_relative_information_score: 3469.2307, mean_absolute_error: 0.0615, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.8807, predictive_accuracy: 0.9385, prior_entropy: 0.3338, recall: 0.9385, relative_absolute_error: 0.5325, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.2481, root_relative_squared_error: 1.0323, scimark_benchmark: 1350.9691, usercpu_time_millis: 525330, usercpu_time_millis_testing: 85100, usercpu_time_millis_training: 440230,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9981, f_measure: 0.9883, kappa: 0.9023, kb_relative_information_score: 11861.172, mean_absolute_error: 0.0127, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9893, predictive_accuracy: 0.9879, prior_entropy: 0.3338, recall: 0.9879, relative_absolute_error: 0.1095, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.1005, root_relative_squared_error: 0.4183, scimark_benchmark: 1304.9611, usercpu_time_millis: 630, usercpu_time_millis_testing: 240, usercpu_time_millis_training: 390,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9988, f_measure: 0.994, kappa: 0.9483, kb_relative_information_score: 13140.4479, mean_absolute_error: 0.0069, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9941, predictive_accuracy: 0.9939, prior_entropy: 0.3338, recall: 0.9939, relative_absolute_error: 0.0596, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.0716, root_relative_squared_error: 0.2978, scimark_benchmark: 935.4444, usercpu_time_millis: 219050, usercpu_time_millis_testing: 181800, usercpu_time_millis_training: 37250,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9989, f_measure: 0.9941, kappa: 0.9488, kb_relative_information_score: 10892.2822, mean_absolute_error: 0.0224, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9941, predictive_accuracy: 0.9942, prior_entropy: 0.3338, recall: 0.9942, relative_absolute_error: 0.1939, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.0795, root_relative_squared_error: 0.3307, scimark_benchmark: 1291.6995, usercpu_time_millis: 5630, usercpu_time_millis_testing: 350, usercpu_time_millis_training: 5280,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9143, f_measure: 0.9815, kappa: 0.8387, kb_relative_information_score: 11119.9012, mean_absolute_error: 0.0184, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9814, predictive_accuracy: 0.9816, prior_entropy: 0.3338, recall: 0.9816, relative_absolute_error: 0.1593, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.1357, root_relative_squared_error: 0.5645, scimark_benchmark: 1313.5726, usercpu_time_millis: 130, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 100,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9868, f_measure: 0.9906, kappa: 0.9192, kb_relative_information_score: 12364.374, mean_absolute_error: 0.0139, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9907, predictive_accuracy: 0.9906, prior_entropy: 0.3338, recall: 0.9906, relative_absolute_error: 0.1199, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.0906, root_relative_squared_error: 0.3769, scimark_benchmark: 1315.3881, usercpu_time_millis: 560, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 540,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9631, f_measure: 0.9915, kappa: 0.9262, kb_relative_information_score: 12668.5046, mean_absolute_error: 0.0117, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9915, predictive_accuracy: 0.9915, prior_entropy: 0.3338, recall: 0.9915, relative_absolute_error: 0.1009, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.0908, root_relative_squared_error: 0.3777, scimark_benchmark: 1321.9426, usercpu_time_millis: 31970, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 31950,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9568, f_measure: 0.9921, kappa: 0.9308, kb_relative_information_score: 12992.5291, mean_absolute_error: 0.0079, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9921, predictive_accuracy: 0.9922, prior_entropy: 0.3338, recall: 0.9922, relative_absolute_error: 0.0679, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.0886, root_relative_squared_error: 0.3687, scimark_benchmark: 1386.5717, usercpu_time_millis: 15730, usercpu_time_millis_testing: 7710, usercpu_time_millis_training: 8020,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.9087, kb_relative_information_score: 3469.2307, mean_absolute_error: 0.0615, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.8807, predictive_accuracy: 0.9385, prior_entropy: 0.3338, recall: 0.9385, relative_absolute_error: 0.5325, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.2481, root_relative_squared_error: 1.0323, scimark_benchmark: 1292.2426, usercpu_time_millis: 1208600, usercpu_time_millis_testing: 199550, usercpu_time_millis_training: 1009050,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9706, f_measure: 0.992, kappa: 0.9305, kb_relative_information_score: 12930.2316, mean_absolute_error: 0.0087, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.992, predictive_accuracy: 0.9919, prior_entropy: 0.3338, recall: 0.9919, relative_absolute_error: 0.0756, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.0873, root_relative_squared_error: 0.3633, scimark_benchmark: 1392.1129, usercpu_time_millis: 2820, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 2800,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7245, f_measure: 0.9443, kappa: 0.4949, kb_relative_information_score: 4996.9008, mean_absolute_error: 0.0529, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9424, predictive_accuracy: 0.9471, prior_entropy: 0.3338, recall: 0.9471, relative_absolute_error: 0.458, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.2301, root_relative_squared_error: 0.9573, scimark_benchmark: 1351.788, usercpu_time_millis: 200, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 180,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9752, f_measure: 0.9903, kappa: 0.9176, kb_relative_information_score: 12635.2514, mean_absolute_error: 0.0099, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9906, predictive_accuracy: 0.9901, prior_entropy: 0.3338, recall: 0.9901, relative_absolute_error: 0.0854, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.0993, root_relative_squared_error: 0.4133, scimark_benchmark: 1353.5686, usercpu_time_millis: 2340, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 2330,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4986, f_measure: 0.9087, kb_relative_information_score: -17.2542, mean_absolute_error: 0.1156, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.8807, predictive_accuracy: 0.9385, prior_entropy: 0.3338, recall: 0.9385, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.2403, root_relative_squared_error: 1, scimark_benchmark: 1358.4955, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9637, f_measure: 0.9929, kappa: 0.9389, kb_relative_information_score: 12956.6684, mean_absolute_error: 0.0092, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9929, predictive_accuracy: 0.9929, prior_entropy: 0.3338, recall: 0.9929, relative_absolute_error: 0.08, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.0831, root_relative_squared_error: 0.3458, scimark_benchmark: 1466.6185, usercpu_time_millis: 2510, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 2500,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9948, f_measure: 0.9927, kappa: 0.9374, kb_relative_information_score: 13039.3353, mean_absolute_error: 0.0075, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9929, predictive_accuracy: 0.9926, prior_entropy: 0.3338, recall: 0.9926, relative_absolute_error: 0.0647, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.0848, root_relative_squared_error: 0.3528, scimark_benchmark: 945.6434, usercpu_time_millis: 58790, usercpu_time_millis_testing: 18390, usercpu_time_millis_training: 40400,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9942, f_measure: 0.9937, kappa: 0.9463, kb_relative_information_score: 13212.1225, mean_absolute_error: 0.0066, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9938, predictive_accuracy: 0.9937, prior_entropy: 0.3338, recall: 0.9937, relative_absolute_error: 0.0567, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.0776, root_relative_squared_error: 0.3229, scimark_benchmark: 876.8277, usercpu_time_millis: 124460, usercpu_time_millis_testing: 39140, usercpu_time_millis_training: 85320,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9966, f_measure: 0.9929, kappa: 0.9386, kb_relative_information_score: 13214.2458, mean_absolute_error: 0.0074, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9929, predictive_accuracy: 0.9929, prior_entropy: 0.3338, recall: 0.9929, relative_absolute_error: 0.0638, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.0769, root_relative_squared_error: 0.3201, scimark_benchmark: 938.4285, usercpu_time_millis: 157770, usercpu_time_millis_testing: 48190, usercpu_time_millis_training: 109580,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9981, f_measure: 0.9924, kappa: 0.934, kb_relative_information_score: 13101.3882, mean_absolute_error: 0.0086, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9924, predictive_accuracy: 0.9924, prior_entropy: 0.3338, recall: 0.9924, relative_absolute_error: 0.0741, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.0782, root_relative_squared_error: 0.3254, scimark_benchmark: 938.2848, usercpu_time_millis: 109030, usercpu_time_millis_testing: 32600, usercpu_time_millis_training: 76430,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9959, f_measure: 0.9915, kappa: 0.9263, kb_relative_information_score: 12888.0104, mean_absolute_error: 0.0087, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9915, predictive_accuracy: 0.9916, prior_entropy: 0.3338, recall: 0.9916, relative_absolute_error: 0.0752, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.0867, root_relative_squared_error: 0.361, scimark_benchmark: 911.3823, usercpu_time_millis: 104170, usercpu_time_millis_testing: 100, usercpu_time_millis_training: 104070,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9964, f_measure: 0.9906, kappa: 0.9192, kb_relative_information_score: 12704.1073, mean_absolute_error: 0.0095, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9907, predictive_accuracy: 0.9906, prior_entropy: 0.3338, recall: 0.9906, relative_absolute_error: 0.0824, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.0931, root_relative_squared_error: 0.3873, scimark_benchmark: 943.2817, usercpu_time_millis: 43370, usercpu_time_millis_testing: 70, usercpu_time_millis_training: 43300,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.994, f_measure: 0.9888, kappa: 0.9025, kb_relative_information_score: 12364.1774, mean_absolute_error: 0.0121, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9888, predictive_accuracy: 0.989, prior_entropy: 0.3338, recall: 0.989, relative_absolute_error: 0.1049, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.0996, root_relative_squared_error: 0.4144, scimark_benchmark: 876.8277, usercpu_time_millis: 16080, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 16050,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9803, f_measure: 0.9865, kappa: 0.8837, kb_relative_information_score: 11782.169, mean_absolute_error: 0.0154, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9866, predictive_accuracy: 0.9865, prior_entropy: 0.3338, recall: 0.9865, relative_absolute_error: 0.1331, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.1118, root_relative_squared_error: 0.4653, scimark_benchmark: 938.4285, usercpu_time_millis: 6580, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 6560,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9848, f_measure: 0.9816, kappa: 0.8445, kb_relative_information_score: 10879.7078, mean_absolute_error: 0.0205, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9823, predictive_accuracy: 0.9811, prior_entropy: 0.3338, recall: 0.9811, relative_absolute_error: 0.1771, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.1331, root_relative_squared_error: 0.5536, scimark_benchmark: 938.9865, usercpu_time_millis: 3400, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 3380,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9991, f_measure: 0.9943, kappa: 0.9512, kb_relative_information_score: 13148.5088, mean_absolute_error: 0.0078, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9944, predictive_accuracy: 0.9943, prior_entropy: 0.3338, recall: 0.9943, relative_absolute_error: 0.0671, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.0678, root_relative_squared_error: 0.2821, scimark_benchmark: 941.7954, usercpu_time_millis: 68510, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 68490,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9984, build_cpu_time: 117.8331, build_memory: 1705207592.812, f_measure: 0.9939, kappa: 0.9473, kb_relative_information_score: 12866.1976, mean_absolute_error: 0.0099, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9939, predictive_accuracy: 0.9939, prior_entropy: 0.3338, recall: 0.9939, relative_absolute_error: 0.0855, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.07, root_relative_squared_error: 0.2913, scimark_benchmark: 938.3548,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9983, build_cpu_time: 56.4893, build_memory: 129449908.3732, f_measure: 0.9938, kappa: 0.9468, kb_relative_information_score: 12833.0149, mean_absolute_error: 0.01, mean_prior_absolute_error: 0.1156, number_of_instances: 14395, precision: 0.9939, predictive_accuracy: 0.9938, prior_entropy: 0.3338, recall: 0.9938, relative_absolute_error: 0.0865, root_mean_prior_squared_error: 0.2403, root_mean_squared_error: 0.0708, root_relative_squared_error: 0.2948, scimark_benchmark: 945.4198,

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

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