Task
Supervised Data Stream Classification on molecular-biology_promoters

Supervised Data Stream Classification on molecular-biology_promoters

Task 2231 Supervised Data Stream Classification molecular-biology_promoters 2 runs submitted
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Joaquin Vanschoren 11 years ago
ran flow moa.WEKAClassifier_SMO_PolyKernel(1) on task Supervised Data Stream Classification on data set molecular-biology_promoters
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.1034, mean_absolute_error: 0.375, mean_prior_absolute_error: 0.375, number_of_instances: 106, precision: 0.0649, predictive_accuracy: 0.2547, prior_entropy: 2, recall: 0.2547, relative_absolute_error: 1, root_mean_prior_squared_error: 0.433, root_mean_squared_error: 0.433, root_relative_squared_error: 1, run_cpu_time: 0.01,
Jan van Rijn 11 years ago
ran flow moa.WEKAClassifier_LinearRegression(1) on task Supervised Data Stream Classification on data set molecular-biology_promoters
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.1034, mean_absolute_error: 0.375, mean_prior_absolute_error: 0.375, number_of_instances: 106, precision: 0.0649, predictive_accuracy: 0.2547, prior_entropy: 2, recall: 0.2547, relative_absolute_error: 1, root_mean_prior_squared_error: 0.433, root_mean_squared_error: 0.433, root_relative_squared_error: 1, run_cpu_time: 0.01,

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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.

    Given inputs

    estimation_procedure Interleaved Test then Train
    source_data molecular-biology_promoters (1)
    target_feature p7

    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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