Task
Supervised Regression on rmftsa_ctoarrivals

Supervised Regression on rmftsa_ctoarrivals

Task 4997 Supervised Regression rmftsa_ctoarrivals 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 rmftsa_ctoarrivals
0 likes - 0 downloads - 0 reach - mean_absolute_error: 30562.8414, mean_prior_absolute_error: 71489.8309, number_of_instances: 264, relative_absolute_error: 0.4275, root_mean_prior_squared_error: 86198.8721, root_mean_squared_error: 40492.8925, root_relative_squared_error: 0.4698, usercpu_time_millis: 0.127, usercpu_time_millis_testing: 0.03, usercpu_time_millis_training: 0.097,
Heidi Seibold 7 years ago
ran flow mlr.regr.rpart(5) on task Supervised Regression on data set rmftsa_ctoarrivals
0 likes - 0 downloads - 0 reach - mean_absolute_error: 20898.8302, mean_prior_absolute_error: 71489.8309, number_of_instances: 264, relative_absolute_error: 0.2923, root_mean_prior_squared_error: 86198.8721, root_mean_squared_error: 28671.744, root_relative_squared_error: 0.3326, usercpu_time_millis: 0.039, usercpu_time_millis_testing: 0.012, usercpu_time_millis_training: 0.027,

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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 rmftsa_ctoarrivals (1)
    target_feature arrivals

    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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