OpenML
Supervised Classification on pollen

Supervised Classification on pollen

Task 4440 Supervised Classification pollen 229 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.4939, kappa: -0.0021, kb_relative_information_score: -0.0332, mean_absolute_error: 0.5, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.4989, predictive_accuracy: 0.499, prior_entropy: 1, recall: 0.499, relative_absolute_error: 1, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5, root_relative_squared_error: 1, scimark_benchmark: 906.0979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4972, f_measure: 0.466, kappa: 0.0018, kb_relative_information_score: 43.2552, mean_absolute_error: 0.4995, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.5012, predictive_accuracy: 0.5009, prior_entropy: 1, recall: 0.5009, relative_absolute_error: 0.999, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5012, root_relative_squared_error: 1.0024, scimark_benchmark: 972.587, usercpu_time_millis: 70, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4981, f_measure: 0.4684, kappa: -0.0007, kb_relative_information_score: 65.7988, mean_absolute_error: 0.4992, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.4995, predictive_accuracy: 0.4996, prior_entropy: 1, recall: 0.4996, relative_absolute_error: 0.9984, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5034, root_relative_squared_error: 1.0068, scimark_benchmark: 931.4089,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5018, f_measure: 0.5015, kappa: 0.0035, kb_relative_information_score: 136, mean_absolute_error: 0.4982, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.5018, predictive_accuracy: 0.5018, prior_entropy: 1, recall: 0.5018, relative_absolute_error: 0.9965, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.7059, root_relative_squared_error: 1.4117, scimark_benchmark: 931.771, usercpu_time_millis: 4790, usercpu_time_millis_testing: 1670, usercpu_time_millis_training: 3120,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5018, f_measure: 0.5015, kappa: 0.0035, kb_relative_information_score: 136, mean_absolute_error: 0.4982, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.5018, predictive_accuracy: 0.5018, prior_entropy: 1, recall: 0.5018, relative_absolute_error: 0.9965, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.7059, root_relative_squared_error: 1.4117, scimark_benchmark: 944.1067, usercpu_time_millis: 4790, usercpu_time_millis_testing: 1630, usercpu_time_millis_training: 3160,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.4939, kappa: -0.0021, kb_relative_information_score: -0.0332, mean_absolute_error: 0.5, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.4989, predictive_accuracy: 0.499, prior_entropy: 1, recall: 0.499, relative_absolute_error: 1, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5, root_relative_squared_error: 1, scimark_benchmark: 938.191, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4938, f_measure: 0.4942, kappa: -0.0116, kb_relative_information_score: -131.1365, mean_absolute_error: 0.5014, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.4942, predictive_accuracy: 0.4942, prior_entropy: 1, recall: 0.4942, relative_absolute_error: 1.0027, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5202, root_relative_squared_error: 1.0405, scimark_benchmark: 938.191, usercpu_time_millis: 470, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 440,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.478, f_measure: 0.4803, kappa: -0.0334, kb_relative_information_score: -90.7553, mean_absolute_error: 0.5008, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.4829, predictive_accuracy: 0.4833, prior_entropy: 1, recall: 0.4833, relative_absolute_error: 1.0017, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5017, root_relative_squared_error: 1.0034, scimark_benchmark: 926.576, usercpu_time_millis: 247460, usercpu_time_millis_testing: 1550, usercpu_time_millis_training: 245910,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4986, f_measure: 0.4904, kappa: -0.0023, kb_relative_information_score: -3.2242, mean_absolute_error: 0.5, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.4988, predictive_accuracy: 0.4989, prior_entropy: 1, recall: 0.4989, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5001, root_relative_squared_error: 1.0001, scimark_benchmark: 905.2959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4924, f_measure: 0.4931, kappa: -0.0133, kb_relative_information_score: -155.3689, mean_absolute_error: 0.5016, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.4933, predictive_accuracy: 0.4933, prior_entropy: 1, recall: 0.4933, relative_absolute_error: 1.0032, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5192, root_relative_squared_error: 1.0384, scimark_benchmark: 905.2959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5018, f_measure: 0.5015, kappa: 0.0035, kb_relative_information_score: 136, mean_absolute_error: 0.4982, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.5018, predictive_accuracy: 0.5018, prior_entropy: 1, recall: 0.5018, relative_absolute_error: 0.9965, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.7059, root_relative_squared_error: 1.4117, scimark_benchmark: 937.5117, usercpu_time_millis: 5070, usercpu_time_millis_testing: 1870, usercpu_time_millis_training: 3200,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5018, f_measure: 0.5015, kappa: 0.0035, kb_relative_information_score: 136, mean_absolute_error: 0.4982, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.5018, predictive_accuracy: 0.5018, prior_entropy: 1, recall: 0.5018, relative_absolute_error: 0.9965, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.7059, root_relative_squared_error: 1.4117, scimark_benchmark: 974.2014, usercpu_time_millis: 4070, usercpu_time_millis_testing: 1600, usercpu_time_millis_training: 2470,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.4939, kappa: -0.0021, kb_relative_information_score: -0.0332, mean_absolute_error: 0.5, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.4989, predictive_accuracy: 0.499, prior_entropy: 1, recall: 0.499, relative_absolute_error: 1, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5, root_relative_squared_error: 1, scimark_benchmark: 947.1781, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4924, f_measure: 0.4931, kappa: -0.0133, kb_relative_information_score: -155.3689, mean_absolute_error: 0.5016, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.4933, predictive_accuracy: 0.4933, prior_entropy: 1, recall: 0.4933, relative_absolute_error: 1.0032, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5192, root_relative_squared_error: 1.0384, scimark_benchmark: 943.1009, usercpu_time_millis: 4110, usercpu_time_millis_testing: 690, usercpu_time_millis_training: 3420,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.4939, kappa: -0.0021, kb_relative_information_score: -0.0332, mean_absolute_error: 0.5, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.4989, predictive_accuracy: 0.499, prior_entropy: 1, recall: 0.499, relative_absolute_error: 1, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5, root_relative_squared_error: 1, scimark_benchmark: 942.2392, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4972, f_measure: 0.466, kappa: 0.0018, kb_relative_information_score: 43.2552, mean_absolute_error: 0.4995, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.5012, predictive_accuracy: 0.5009, prior_entropy: 1, recall: 0.5009, relative_absolute_error: 0.999, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5012, root_relative_squared_error: 1.0024, scimark_benchmark: 908.9569, usercpu_time_millis: 80, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4981, f_measure: 0.4684, kappa: -0.0007, kb_relative_information_score: 65.7988, mean_absolute_error: 0.4992, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.4995, predictive_accuracy: 0.4996, prior_entropy: 1, recall: 0.4996, relative_absolute_error: 0.9984, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5034, root_relative_squared_error: 1.0068, scimark_benchmark: 938.1282, usercpu_time_millis: 230, usercpu_time_millis_training: 230,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5018, f_measure: 0.5015, kappa: 0.0035, kb_relative_information_score: 136, mean_absolute_error: 0.4982, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.5018, predictive_accuracy: 0.5018, prior_entropy: 1, recall: 0.5018, relative_absolute_error: 0.9965, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.7059, root_relative_squared_error: 1.4117, scimark_benchmark: 943.6618, usercpu_time_millis: 4900, usercpu_time_millis_testing: 1610, usercpu_time_millis_training: 3290,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4988, f_measure: 0.4939, kappa: -0.0021, kb_relative_information_score: -0.0332, mean_absolute_error: 0.5, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.4989, predictive_accuracy: 0.499, prior_entropy: 1, recall: 0.499, relative_absolute_error: 1, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5, root_relative_squared_error: 1, scimark_benchmark: 941.4991, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4938, f_measure: 0.4942, kappa: -0.0116, kb_relative_information_score: -131.1365, mean_absolute_error: 0.5014, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.4942, predictive_accuracy: 0.4942, prior_entropy: 1, recall: 0.4942, relative_absolute_error: 1.0027, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5202, root_relative_squared_error: 1.0405, scimark_benchmark: 903.2737, usercpu_time_millis: 450, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 420,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.478, f_measure: 0.4803, kappa: -0.0334, kb_relative_information_score: -90.7553, mean_absolute_error: 0.5008, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.4829, predictive_accuracy: 0.4833, prior_entropy: 1, recall: 0.4833, relative_absolute_error: 1.0017, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5017, root_relative_squared_error: 1.0034, scimark_benchmark: 930.404, usercpu_time_millis: 222610, usercpu_time_millis_testing: 1420, usercpu_time_millis_training: 221190,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4986, f_measure: 0.4904, kappa: -0.0023, kb_relative_information_score: -3.2242, mean_absolute_error: 0.5, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.4988, predictive_accuracy: 0.4989, prior_entropy: 1, recall: 0.4989, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5001, root_relative_squared_error: 1.0001, scimark_benchmark: 936.9595, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4924, f_measure: 0.4931, kappa: -0.0133, kb_relative_information_score: -155.3689, mean_absolute_error: 0.5016, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.4933, predictive_accuracy: 0.4933, prior_entropy: 1, recall: 0.4933, relative_absolute_error: 1.0032, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5192, root_relative_squared_error: 1.0384, scimark_benchmark: 917.5013, usercpu_time_millis: 5250, usercpu_time_millis_testing: 1220, usercpu_time_millis_training: 4030,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4967, f_measure: 0.4914, kappa: -0.0041, kb_relative_information_score: -0.6771, mean_absolute_error: 0.5, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.4979, predictive_accuracy: 0.498, prior_entropy: 1, recall: 0.498, relative_absolute_error: 1, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5, root_relative_squared_error: 1, scimark_benchmark: 908.9569, usercpu_time_millis: 13080, usercpu_time_millis_testing: 8390, usercpu_time_millis_training: 4690,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4974, f_measure: 0.4905, kappa: -0.0035, kb_relative_information_score: -0.6026, mean_absolute_error: 0.5, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.4981, predictive_accuracy: 0.4983, prior_entropy: 1, recall: 0.4983, relative_absolute_error: 1, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5, root_relative_squared_error: 1, scimark_benchmark: 906.5979, usercpu_time_millis: 2860, usercpu_time_millis_testing: 930, usercpu_time_millis_training: 1930,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.497, f_measure: 0.4914, kappa: -0.0039, kb_relative_information_score: -0.8093, mean_absolute_error: 0.5, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.4979, predictive_accuracy: 0.4981, prior_entropy: 1, recall: 0.4981, relative_absolute_error: 1, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5, root_relative_squared_error: 1, scimark_benchmark: 921.466, usercpu_time_millis: 1350, usercpu_time_millis_testing: 460, usercpu_time_millis_training: 890,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4976, f_measure: 0.4926, kappa: -0.0032, kb_relative_information_score: -0.598, mean_absolute_error: 0.5, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.4983, predictive_accuracy: 0.4984, prior_entropy: 1, recall: 0.4984, relative_absolute_error: 1, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5, root_relative_squared_error: 1, scimark_benchmark: 944.235, usercpu_time_millis: 650, usercpu_time_millis_testing: 220, usercpu_time_millis_training: 430,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4977, f_measure: 0.4925, kappa: -0.0032, kb_relative_information_score: -0.9689, mean_absolute_error: 0.5, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.4983, predictive_accuracy: 0.4984, prior_entropy: 1, recall: 0.4984, relative_absolute_error: 1, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5, root_relative_squared_error: 1, scimark_benchmark: 905.3417, usercpu_time_millis: 330, usercpu_time_millis_testing: 110, usercpu_time_millis_training: 220,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4986, f_measure: 0.4841, kappa: -0.0022, kb_relative_information_score: 132.6101, mean_absolute_error: 0.4984, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.4988, predictive_accuracy: 0.4989, prior_entropy: 1, recall: 0.4989, relative_absolute_error: 0.9967, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5016, root_relative_squared_error: 1.0033, scimark_benchmark: 941.9549, usercpu_time_millis: 90, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4986, f_measure: 0.4841, kappa: -0.0022, kb_relative_information_score: 132.6101, mean_absolute_error: 0.4984, mean_prior_absolute_error: 0.5, number_of_instances: 38480, precision: 0.4988, predictive_accuracy: 0.4989, prior_entropy: 1, recall: 0.4989, relative_absolute_error: 0.9967, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5016, root_relative_squared_error: 1.0033, scimark_benchmark: 930.0565, usercpu_time_millis: 90, usercpu_time_millis_training: 90,
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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

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From your own software

Use one of our APIs to download data from OpenML and upload your results

OpenML APIs