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|Created||Wed, 27 Jul 2016 14:37:04 +0000|
|Published||Wed, 27 Jul 2016 14:45:34 +0000|
The objective of this script is to perform a k-fold cross validation of a model built from a dataset. The algorithm:
Divides the dataset in k parts
Holds out the data in one of the parts and builds a model with the rest of data
Evaluates the model with the hold out data
The second and third steps are repeated with each of the k parts, so that k evaluations are generated
Finally, the evaluation metrics are averaged to provide the cross-validation metrics.
The output of the script will be an
evaluation ID. This evaluation is a cross-validation, meaning that its metrics are averages of the k evaluations created in the cross-validation process.