Task
Supervised Regression on cloud

Supervised Regression on cloud

Task 2301 Supervised Regression cloud 5 runs submitted
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Nico Strasdat 6 years ago
ran flow sklearn.pipeline.Pipeline(scal ... hpo4svm.hpo.sklearn.HPOSVM)(1) on task Supervised Regression on data set cloud
0 likes - 0 downloads - 0 reach - mean_absolute_error: 0.268, mean_prior_absolute_error: 0.7807, number_of_instances: 108, relative_absolute_error: 0.3432, root_mean_prior_squared_error: 1.0722, root_mean_squared_error: 0.4302, root_relative_squared_error: 0.4012,
Heidi Seibold 7 years ago
ran flow mlr.regr.rpart.dummied(1) on task Supervised Regression on data set cloud
0 likes - 0 downloads - 0 reach - mean_absolute_error: 0.4117, mean_prior_absolute_error: 0.7807, number_of_instances: 108, relative_absolute_error: 0.5273, root_mean_prior_squared_error: 1.0722, root_mean_squared_error: 0.6255, root_relative_squared_error: 0.5834, usercpu_time_millis: 0.119, usercpu_time_millis_testing: 0.033, usercpu_time_millis_training: 0.086,
Heidi Seibold 7 years ago
ran flow mlr.regr.rpart(5) on task Supervised Regression on data set cloud
0 likes - 0 downloads - 0 reach - mean_absolute_error: 0.4117, mean_prior_absolute_error: 0.7807, number_of_instances: 108, relative_absolute_error: 0.5273, root_mean_prior_squared_error: 1.0722, root_mean_squared_error: 0.6255, root_relative_squared_error: 0.5834, usercpu_time_millis: 0.058, usercpu_time_millis_testing: 0.022, usercpu_time_millis_training: 0.036,
Heidi Seibold 7 years ago
ran flow mlr.regr.rpart.dummied(1) on task Supervised Regression on data set cloud
0 likes - 0 downloads - 0 reach - mean_absolute_error: 0.4117, mean_prior_absolute_error: 0.7807, number_of_instances: 108, relative_absolute_error: 0.5273, root_mean_prior_squared_error: 1.0722, root_mean_squared_error: 0.6255, root_relative_squared_error: 0.5834, usercpu_time_millis: 0.126, usercpu_time_millis_testing: 0.038, usercpu_time_millis_training: 0.088,
Heidi Seibold 7 years ago
ran flow mlr.regr.rpart(5) on task Supervised Regression on data set cloud
0 likes - 0 downloads - 0 reach - mean_absolute_error: 0.4117, mean_prior_absolute_error: 0.7807, number_of_instances: 108, relative_absolute_error: 0.5273, root_mean_prior_squared_error: 1.0722, root_mean_squared_error: 0.6255, root_relative_squared_error: 0.5834, usercpu_time_millis: 0.055, usercpu_time_millis_testing: 0.017, usercpu_time_millis_training: 0.038,

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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 cloud (1)
    target_feature TE

    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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