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|Created||Tue, 6 Mar 2018 18:04:57 +0000|
|Published||Tue, 20 Mar 2018 14:19:44 +0000|
The objective of this script is to perform a k-fold cross validation of a deepnet built from a dataset. The algorithm:
- Divides the dataset in k parts
- Holds out the data in one of the parts and builds a deepnet with the rest of data
- Evaluates the deepnet 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.
For more information, please see the readme.