Task
Supervised Regression on analcatdata_chlamydia

Supervised Regression on analcatdata_chlamydia

Task 4860 Supervised Regression analcatdata_chlamydia 2 runs submitted
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Heidi Seibold 7 years ago
ran flow mlr.regr.rpart.dummied(1) on task Supervised Regression on data set analcatdata_chlamydia
0 likes - 0 downloads - 0 reach - mean_absolute_error: 4101.9344, mean_prior_absolute_error: 4909.8886, number_of_instances: 100, relative_absolute_error: 0.8354, root_mean_prior_squared_error: 9512.7992, root_mean_squared_error: 8734.3929, root_relative_squared_error: 0.9182, usercpu_time_millis: 0.152, usercpu_time_millis_testing: 0.048, usercpu_time_millis_training: 0.104,
Heidi Seibold 7 years ago
ran flow mlr.regr.rpart(5) on task Supervised Regression on data set analcatdata_chlamydia
0 likes - 0 downloads - 0 reach - mean_absolute_error: 4029.22, mean_prior_absolute_error: 4909.8886, number_of_instances: 100, relative_absolute_error: 0.8206, root_mean_prior_squared_error: 9512.7992, root_mean_squared_error: 8434.5937, root_relative_squared_error: 0.8867, usercpu_time_millis: 0.045, usercpu_time_millis_testing: 0.016, usercpu_time_millis_training: 0.029,

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    Challenge

    Given a dataset with a numeric target and a set of train/test splits, e.g. generated by a cross-validation procedure, train a model and return the predictions of that model.

    Given inputs

    estimation_procedure 10-fold Crossvalidation
    evaluation_measures mean_absolute_error
    source_data analcatdata_chlamydia (1)
    target_feature Count

    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)

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