Description
Add TrainValidationSplit for hyper-parameter tuning. It randomly splits the input dataset into train and validation and use evaluation metric on the validation set to select the best model. It should be similar to CrossValidator, but simpler and less expensive.
Attachments
Issue Links
- relates to
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SPARK-8971 Support balanced class labels when splitting train/cross validation sets
- Resolved
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SPARK-8983 ML Tuning Cross-Validation Improvements
- Resolved
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SPARK-9910 User guide for train validation split
- Resolved
- links to