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Function: require_once

OpenML
Task
Supervised Classification on fri_c3_100_5

Supervised Classification on fri_c3_100_5

Task 3779 Supervised Classification fri_c3_100_5 956 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 study_7 under100k under1m
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956 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8598, f_measure: 0.8074, kappa: 0.6078, kb_relative_information_score: 53.2102, mean_absolute_error: 0.2353, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.8131, predictive_accuracy: 0.81, prior_entropy: 0.99, recall: 0.81, relative_absolute_error: 0.4773, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.3824, root_relative_squared_error: 0.7704, scimark_benchmark: 1363.454, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5917, f_measure: 0.559, kappa: 0.1737, kb_relative_information_score: 12.2168, mean_absolute_error: 0.43, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.6136, predictive_accuracy: 0.57, prior_entropy: 0.99, recall: 0.57, relative_absolute_error: 0.8723, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.6557, root_relative_squared_error: 1.321, scimark_benchmark: 1318.1432, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4021, kb_relative_information_score: 10.1763, mean_absolute_error: 0.44, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.3136, predictive_accuracy: 0.56, prior_entropy: 0.99, recall: 0.56, relative_absolute_error: 0.8926, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.6633, root_relative_squared_error: 1.3363, scimark_benchmark: 1333.5799,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.668, f_measure: 0.6764, kappa: 0.341, kb_relative_information_score: 34.6626, mean_absolute_error: 0.32, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.6779, predictive_accuracy: 0.68, prior_entropy: 0.99, recall: 0.68, relative_absolute_error: 0.6492, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.5657, root_relative_squared_error: 1.1396, scimark_benchmark: 1287.514,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7297, f_measure: 0.659, kappa: 0.3067, kb_relative_information_score: 18.2374, mean_absolute_error: 0.4131, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.6586, predictive_accuracy: 0.66, prior_entropy: 0.99, recall: 0.66, relative_absolute_error: 0.838, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.4586, root_relative_squared_error: 0.9238, scimark_benchmark: 1386.5717, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6591, f_measure: 0.6671, kappa: 0.3221, kb_relative_information_score: 32.6221, mean_absolute_error: 0.33, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.6676, predictive_accuracy: 0.67, prior_entropy: 0.99, recall: 0.67, relative_absolute_error: 0.6695, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.5745, root_relative_squared_error: 1.1573, scimark_benchmark: 935.5075,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7541, f_measure: 0.6671, kappa: 0.3221, kb_relative_information_score: 21.5889, mean_absolute_error: 0.3999, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.6676, predictive_accuracy: 0.67, prior_entropy: 0.99, recall: 0.67, relative_absolute_error: 0.8112, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.4462, root_relative_squared_error: 0.899, scimark_benchmark: 942.9708, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7971, f_measure: 0.8, kappa: 0.5942, kb_relative_information_score: 59.1489, mean_absolute_error: 0.2, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.8, predictive_accuracy: 0.8, prior_entropy: 0.99, recall: 0.8, relative_absolute_error: 0.4057, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.4472, root_relative_squared_error: 0.9009, scimark_benchmark: 918.6491, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.75, f_measure: 0.72, kappa: 0.4318, kb_relative_information_score: 31.7331, mean_absolute_error: 0.3448, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.72, predictive_accuracy: 0.72, prior_entropy: 0.99, recall: 0.72, relative_absolute_error: 0.6996, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.46, root_relative_squared_error: 0.9267, scimark_benchmark: 934.0566,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.765, f_measure: 0.72, kappa: 0.4318, kb_relative_information_score: 34.0128, mean_absolute_error: 0.3334, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.72, predictive_accuracy: 0.72, prior_entropy: 0.99, recall: 0.72, relative_absolute_error: 0.6763, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.4529, root_relative_squared_error: 0.9125, scimark_benchmark: 935.4444,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7606, f_measure: 0.72, kappa: 0.4318, kb_relative_information_score: 33.4583, mean_absolute_error: 0.3363, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.72, predictive_accuracy: 0.72, prior_entropy: 0.99, recall: 0.72, relative_absolute_error: 0.6821, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.4551, root_relative_squared_error: 0.9168, scimark_benchmark: 944.529,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7614, f_measure: 0.7303, kappa: 0.4534, kb_relative_information_score: 38.9054, mean_absolute_error: 0.3086, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.7307, predictive_accuracy: 0.73, prior_entropy: 0.99, recall: 0.73, relative_absolute_error: 0.626, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.46, root_relative_squared_error: 0.9266, scimark_benchmark: 940.6207, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9134, f_measure: 0.8292, kappa: 0.6525, kb_relative_information_score: 52.3467, mean_absolute_error: 0.2469, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.83, predictive_accuracy: 0.83, prior_entropy: 0.99, recall: 0.83, relative_absolute_error: 0.5009, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.3437, root_relative_squared_error: 0.6924, scimark_benchmark: 1280.6952, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7744, f_measure: 0.7794, kappa: 0.5514, kb_relative_information_score: 55.0679, mean_absolute_error: 0.22, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.7794, predictive_accuracy: 0.78, prior_entropy: 0.99, recall: 0.78, relative_absolute_error: 0.4463, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.469, root_relative_squared_error: 0.9449, scimark_benchmark: 1333.5799,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6459, f_measure: 0.6522, kappa: 0.3014, kb_relative_information_score: 24.4182, mean_absolute_error: 0.3793, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.6778, predictive_accuracy: 0.67, prior_entropy: 0.99, recall: 0.67, relative_absolute_error: 0.7694, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.5148, root_relative_squared_error: 1.0371, scimark_benchmark: 1369.9744,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7591, f_measure: 0.7593, kappa: 0.5106, kb_relative_information_score: 46.0474, mean_absolute_error: 0.2717, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.7592, predictive_accuracy: 0.76, prior_entropy: 0.99, recall: 0.76, relative_absolute_error: 0.5512, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.4592, root_relative_squared_error: 0.9251, scimark_benchmark: 1309.3173, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7565, f_measure: 0.76, kappa: 0.513, kb_relative_information_score: 50.9868, mean_absolute_error: 0.24, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.76, predictive_accuracy: 0.76, prior_entropy: 0.99, recall: 0.76, relative_absolute_error: 0.4869, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.4899, root_relative_squared_error: 0.9869, scimark_benchmark: 1341.5768,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5909, f_measure: 0.4989, kappa: 0.166, kb_relative_information_score: 8.1357, mean_absolute_error: 0.45, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.6785, predictive_accuracy: 0.55, prior_entropy: 0.99, recall: 0.55, relative_absolute_error: 0.9129, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.6708, root_relative_squared_error: 1.3514, scimark_benchmark: 1290.1085,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7786, f_measure: 0.7907, kappa: 0.579, kb_relative_information_score: 51.2008, mean_absolute_error: 0.2466, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.7954, predictive_accuracy: 0.79, prior_entropy: 0.99, recall: 0.79, relative_absolute_error: 0.5004, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.4256, root_relative_squared_error: 0.8573, scimark_benchmark: 1358.4523,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7183, f_measure: 0.7206, kappa: 0.4346, kb_relative_information_score: 42.8247, mean_absolute_error: 0.28, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.7217, predictive_accuracy: 0.72, prior_entropy: 0.99, recall: 0.72, relative_absolute_error: 0.568, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.5292, root_relative_squared_error: 1.066, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7427, f_measure: 0.7488, kappa: 0.489, kb_relative_information_score: 48.9463, mean_absolute_error: 0.25, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.7491, predictive_accuracy: 0.75, prior_entropy: 0.99, recall: 0.75, relative_absolute_error: 0.5072, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.5, root_relative_squared_error: 1.0073, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4513, f_measure: 0.4021, kb_relative_information_score: -0.1765, mean_absolute_error: 0.4935, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.3136, predictive_accuracy: 0.56, prior_entropy: 0.99, recall: 0.56, relative_absolute_error: 1.0011, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.4969, root_relative_squared_error: 1.0011, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7567, f_measure: 0.7906, kappa: 0.577, kb_relative_information_score: 49.8669, mean_absolute_error: 0.2535, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.7926, predictive_accuracy: 0.79, prior_entropy: 0.99, recall: 0.79, relative_absolute_error: 0.5142, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.4393, root_relative_squared_error: 0.8851, scimark_benchmark: 1605.6303,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7768, f_measure: 0.7357, kappa: 0.4619, kb_relative_information_score: 41.3664, mean_absolute_error: 0.2931, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.7413, predictive_accuracy: 0.74, prior_entropy: 0.99, recall: 0.74, relative_absolute_error: 0.5946, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.4574, root_relative_squared_error: 0.9214, scimark_benchmark: 927.0753, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7628, f_measure: 0.7451, kappa: 0.4813, kb_relative_information_score: 34.781, mean_absolute_error: 0.3332, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.753, predictive_accuracy: 0.75, prior_entropy: 0.99, recall: 0.75, relative_absolute_error: 0.6759, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.4393, root_relative_squared_error: 0.8849, scimark_benchmark: 945.6434,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7287, f_measure: 0.7247, kappa: 0.4398, kb_relative_information_score: 29.1659, mean_absolute_error: 0.3616, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.7318, predictive_accuracy: 0.73, prior_entropy: 0.99, recall: 0.73, relative_absolute_error: 0.7335, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.4499, root_relative_squared_error: 0.9063, scimark_benchmark: 876.8277, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7287, f_measure: 0.7247, kappa: 0.4398, kb_relative_information_score: 29.1659, mean_absolute_error: 0.3616, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.7318, predictive_accuracy: 0.73, prior_entropy: 0.99, recall: 0.73, relative_absolute_error: 0.7335, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.4499, root_relative_squared_error: 0.9063, scimark_benchmark: 945.6434,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7287, f_measure: 0.7247, kappa: 0.4398, kb_relative_information_score: 29.1659, mean_absolute_error: 0.3616, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.7318, predictive_accuracy: 0.73, prior_entropy: 0.99, recall: 0.73, relative_absolute_error: 0.7335, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.4499, root_relative_squared_error: 0.9063, scimark_benchmark: 894.7455, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9172, f_measure: 0.8389, kappa: 0.6721, kb_relative_information_score: 67.9207, mean_absolute_error: 0.1572, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.8407, predictive_accuracy: 0.84, prior_entropy: 0.99, recall: 0.84, relative_absolute_error: 0.3189, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.3771, root_relative_squared_error: 0.7597, scimark_benchmark: 936.7115, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9152, f_measure: 0.8395, kappa: 0.6737, kb_relative_information_score: 65.6706, mean_absolute_error: 0.169, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.8398, predictive_accuracy: 0.84, prior_entropy: 0.99, recall: 0.84, relative_absolute_error: 0.3429, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.3775, root_relative_squared_error: 0.7605, scimark_benchmark: 943.2817, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8789, f_measure: 0.7697, kappa: 0.5321, kb_relative_information_score: 55.7634, mean_absolute_error: 0.2155, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.7695, predictive_accuracy: 0.77, prior_entropy: 0.99, recall: 0.77, relative_absolute_error: 0.4371, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.4181, root_relative_squared_error: 0.8423, scimark_benchmark: 936.6206, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8204, f_measure: 0.7488, kappa: 0.489, kb_relative_information_score: 46.634, mean_absolute_error: 0.2633, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.7491, predictive_accuracy: 0.75, prior_entropy: 0.99, recall: 0.75, relative_absolute_error: 0.534, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.4453, root_relative_squared_error: 0.897, scimark_benchmark: 933.8635,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7551, f_measure: 0.6908, kappa: 0.3755, kb_relative_information_score: 37.0796, mean_absolute_error: 0.3114, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.6929, predictive_accuracy: 0.69, prior_entropy: 0.99, recall: 0.69, relative_absolute_error: 0.6318, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.4877, root_relative_squared_error: 0.9825, scimark_benchmark: 938.9865, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9259, f_measure: 0.8298, kappa: 0.6542, kb_relative_information_score: 65.6475, mean_absolute_error: 0.1683, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.8297, predictive_accuracy: 0.83, prior_entropy: 0.99, recall: 0.83, relative_absolute_error: 0.3414, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.378, root_relative_squared_error: 0.7614, scimark_benchmark: 933.8635, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9261, f_measure: 0.8395, kappa: 0.6737, kb_relative_information_score: 65.3483, mean_absolute_error: 0.1722, mean_prior_absolute_error: 0.4929, number_of_instances: 100, precision: 0.8398, predictive_accuracy: 0.84, prior_entropy: 0.99, recall: 0.84, relative_absolute_error: 0.3492, root_mean_prior_squared_error: 0.4964, root_mean_squared_error: 0.3635, root_relative_squared_error: 0.7324, scimark_benchmark: 924.6116, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
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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

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