Task
Supervised Regression on echoMonths

Supervised Regression on echoMonths

Task 2310 Supervised Regression echoMonths 10 runs submitted
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Heidi Seibold 8 years ago
ran flow mlr.regr.develpartykit.cforest(5) on task Supervised Regression on data set echoMonths
0 likes - 0 downloads - 0 reach - mean_absolute_error: 9.6687, mean_prior_absolute_error: 13.2912, number_of_instances: 130, relative_absolute_error: 0.7275, root_mean_prior_squared_error: 15.7972, root_mean_squared_error: 11.9925, root_relative_squared_error: 0.7592,
Heidi Seibold 8 years ago
ran flow mlr.regr.develpartykit.ctree(4) on task Supervised Regression on data set echoMonths
0 likes - 0 downloads - 0 reach - mean_absolute_error: 9.0915, mean_prior_absolute_error: 13.2912, number_of_instances: 130, relative_absolute_error: 0.684, root_mean_prior_squared_error: 15.7972, root_mean_squared_error: 11.803, root_relative_squared_error: 0.7472,
Heidi Seibold 8 years ago
ran flow mlr.regr.develpartykit.cforest(5) on task Supervised Regression on data set echoMonths
0 likes - 0 downloads - 0 reach - mean_absolute_error: 8.952, mean_prior_absolute_error: 13.2912, number_of_instances: 130, relative_absolute_error: 0.6735, root_mean_prior_squared_error: 15.7972, root_mean_squared_error: 11.3828, root_relative_squared_error: 0.7206,
Heidi Seibold 8 years ago
ran flow mlr.regr.develpartykit.ctree(4) on task Supervised Regression on data set echoMonths
0 likes - 0 downloads - 0 reach - mean_absolute_error: 8.9423, mean_prior_absolute_error: 13.2912, number_of_instances: 130, relative_absolute_error: 0.6728, root_mean_prior_squared_error: 15.7972, root_mean_squared_error: 11.3711, root_relative_squared_error: 0.7198,
Heidi Seibold 8 years ago
ran flow mlr.regr.develpartykit.ctree(4) on task Supervised Regression on data set echoMonths
0 likes - 0 downloads - 0 reach - mean_absolute_error: 8.9423, mean_prior_absolute_error: 13.2912, number_of_instances: 130, relative_absolute_error: 0.6728, root_mean_prior_squared_error: 15.7972, root_mean_squared_error: 11.3711, root_relative_squared_error: 0.7198,
Heidi Seibold 8 years ago
ran flow mlr.regr.develpartykit.cforest(5) on task Supervised Regression on data set echoMonths
0 likes - 0 downloads - 0 reach - mean_absolute_error: 8.9519, mean_prior_absolute_error: 13.2912, number_of_instances: 130, relative_absolute_error: 0.6735, root_mean_prior_squared_error: 15.7972, root_mean_squared_error: 11.3828, root_relative_squared_error: 0.7206,
Heidi Seibold 8 years ago
ran flow mlr.regr.develpartykit.cforest(5) on task Supervised Regression on data set echoMonths
0 likes - 0 downloads - 0 reach - mean_absolute_error: 8.9593, mean_prior_absolute_error: 13.2912, number_of_instances: 130, relative_absolute_error: 0.6741, root_mean_prior_squared_error: 15.7972, root_mean_squared_error: 11.443, root_relative_squared_error: 0.7244,
Heidi Seibold 8 years ago
ran flow mlr.regr.develpartykit.ctree(4) on task Supervised Regression on data set echoMonths
0 likes - 0 downloads - 0 reach - mean_absolute_error: 9.2291, mean_prior_absolute_error: 13.2912, number_of_instances: 130, relative_absolute_error: 0.6944, root_mean_prior_squared_error: 15.7972, root_mean_squared_error: 11.7351, root_relative_squared_error: 0.7429,
Heidi Seibold 8 years ago
ran flow mlr.regr.develpartykit.cforest(5) on task Supervised Regression on data set echoMonths
0 likes - 0 downloads - 0 reach - mean_absolute_error: 8.9519, mean_prior_absolute_error: 13.2912, number_of_instances: 130, relative_absolute_error: 0.6735, root_mean_prior_squared_error: 15.7972, root_mean_squared_error: 11.3828, root_relative_squared_error: 0.7206,
Heidi Seibold 8 years ago
ran flow mlr.regr.develpartykit.ctree(4) on task Supervised Regression on data set echoMonths
0 likes - 0 downloads - 0 reach - mean_absolute_error: 8.9423, mean_prior_absolute_error: 13.2912, number_of_instances: 130, relative_absolute_error: 0.6728, root_mean_prior_squared_error: 15.7972, root_mean_squared_error: 11.3711, root_relative_squared_error: 0.7198,

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    Note: The leaderboard ignores resubmissions of previous solutions, as well as parameter variations that do not improve performance.

    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 echoMonths (1)
    target_feature class

    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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