Github user zapletal-martin commented on the pull request:
https://github.com/apache/spark/pull/7337#issuecomment-120409916
Both CrossValidator and TrainValidationSplit use sampling to split the data
to training and validation.
Currently CrossValidator does
* numFolds = 1 - not valid
* numFolds = 2 - 0.0 to 0.5 training, 0.5 to 1 validation and 0.0 to 0.5
validation and 0.5 to 1 training
TrainValidationSplit does
* 0.0 to trainRatio training, trainRatio to 1 validation
Therefore the logic is different and using TrainValidationSplit is not the
same as just calling CrossValidator. Please let me know if the logic
implemented by TrainValidationSplit is what was expected. We can then
potentially address the code duplication.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
