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More control over model train/test/holdout data cuts

Given that model can be affected by the set of data used for training it, it would be nice to have better control over how the data is split up.

A fairly easy improvement is to allow the user to set a seed for controlling the splits, so you can replicate the split in the future.

A more complex change is to allow the user to specify how may different variations of the train/test split to generate and run models against, either combining the results into an ensemble or selecting the best of the variations as the "final" result.



  • Guest
  • Dec 14 2018
  • Under Consideration
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