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Supervised Data Stream Classification on Stagger2

Supervised Data Stream Classification on Stagger2

Task 7311 Supervised Data Stream Classification Stagger2 306 runs submitted
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  • binstreams ecmlpkdd2015 streamensembles streams study_11 study_16
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 1, kappa: 1, kb_relative_information_score: 999534.5645, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.5, number_of_instances: 1000000, precision: 1, predictive_accuracy: 1, prior_entropy: 1, recall: 1, relative_absolute_error: 0.0006, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.007, root_relative_squared_error: 0.014,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 1, kappa: 1, kb_relative_information_score: 999948.5309, mean_absolute_error: 0, mean_prior_absolute_error: 0.5, number_of_instances: 1000000, precision: 1, predictive_accuracy: 1, prior_entropy: 1, recall: 1, relative_absolute_error: 0.0001, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.0028, root_relative_squared_error: 0.0056,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 1, kappa: 1, kb_relative_information_score: 999864.7872, mean_absolute_error: 0.0001, mean_prior_absolute_error: 0.5, number_of_instances: 1000000, precision: 1, predictive_accuracy: 1, prior_entropy: 1, recall: 1, relative_absolute_error: 0.0002, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.0052, root_relative_squared_error: 0.0104,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 1, kappa: 1, kb_relative_information_score: 999536.3935, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.5, number_of_instances: 1000000, precision: 1, predictive_accuracy: 1, prior_entropy: 1, recall: 1, relative_absolute_error: 0.0006, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.0072, root_relative_squared_error: 0.0144,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8741, f_measure: 0.8852, kappa: 0.7676, kb_relative_information_score: 776300, mean_absolute_error: 0.1119, mean_prior_absolute_error: 0.5, number_of_instances: 1000000, precision: 0.9067, predictive_accuracy: 0.8882, prior_entropy: 1, recall: 0.8882, relative_absolute_error: 0.2237, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.3344, root_relative_squared_error: 0.6689,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 1, kappa: 1, kb_relative_information_score: 883020.4135, mean_absolute_error: 0.0741, mean_prior_absolute_error: 0.5, number_of_instances: 1000000, precision: 1, predictive_accuracy: 1, prior_entropy: 1, recall: 1, relative_absolute_error: 0.1482, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.1112, root_relative_squared_error: 0.2224,

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Challenge

Given a dataset with a nominal target, various data samples of increasing size are defined. A model is build for each individual data sample; from this a learning curve can be drawn.

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Expected outputs

evaluations A list of user-defined evaluations of the task as key-value pairs. KeyValue (optional)
predictions The desired output format Predictions (optional)

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