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Supervised Data Stream Classification on BNG(mushroom)

Supervised Data Stream Classification on BNG(mushroom)

Task 160 Supervised Data Stream Classification BNG(mushroom) 304 runs submitted
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  • binstreams ecmlpkdd2015 streamensembles streams streams-full study_11 study_16
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304 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9948, f_measure: 0.9641, kappa: 0.9281, kb_relative_information_score: 911406.9267, mean_absolute_error: 0.0462, mean_prior_absolute_error: 0.5, number_of_instances: 1000000, precision: 0.9641, predictive_accuracy: 0.9641, prior_entropy: 1, ram_hours: 0, recall: 0.9641, relative_absolute_error: 0.0923, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.158, root_relative_squared_error: 0.316, run_cpu_time: 419.75,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9983, f_measure: 0.989, kappa: 0.9779, kb_relative_information_score: 972504.346, mean_absolute_error: 0.0146, mean_prior_absolute_error: 0.5, number_of_instances: 1000000, precision: 0.989, predictive_accuracy: 0.989, prior_entropy: 1, ram_hours: 0, recall: 0.989, relative_absolute_error: 0.0293, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.0944, root_relative_squared_error: 0.1889, run_cpu_time: 14.19,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9122, f_measure: 0.9132, kappa: 0.8261, kb_relative_information_score: 826708, mean_absolute_error: 0.0866, mean_prior_absolute_error: 0.5, number_of_instances: 1000000, precision: 0.9144, predictive_accuracy: 0.9134, prior_entropy: 1, ram_hours: 0, recall: 0.9134, relative_absolute_error: 0.1733, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.2944, root_relative_squared_error: 0.5887, run_cpu_time: 6.24,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9895, f_measure: 0.927, kappa: 0.8539, kb_relative_information_score: 852415.7375, mean_absolute_error: 0.0741, mean_prior_absolute_error: 0.5, number_of_instances: 1000000, precision: 0.9324, predictive_accuracy: 0.9274, prior_entropy: 1, ram_hours: 0, recall: 0.9274, relative_absolute_error: 0.1482, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.247, root_relative_squared_error: 0.4941, run_cpu_time: 11.49,

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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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