Task type
All Machine Learning Challenge tasks

Machine Learning Challenge

This is a standard machine learning challenge with a hidden private dataset. It offers a labeled training set and an unlabeled test set. The task is to label the unlabeled instances. Only the OpenML server knows the correct labels, and will evaluate the submitted predictions using these hidden labels. The evaluation procedure, measure, and cost function (if any) are provided.


cost_matrix CostMatrix A matrix describing the cost of miss-classifications per type. optional
estimation_procedure Estimation Procedure The estimation procedure used to validate the generated models required
evaluation_measures String The evaluation measures to optimize for, e.g., cpu time, accuracy optional
source_data Dataset The input data for this task required
source_data_labeled Dataset The labelled version of the dataset required
target_feature String The name of the dataset feature to be used as the target feature. required


evaluations KeyValue A list of user-defined evaluations of the task as key-value pairs. optional
model File A file containing the model built on all the input data. optional
predictions Predictions The desired output format optional


Author(s)"Jan van Rijn","Joaquin Vanschoren"