[jira] [Created] (IGNITE-12685) [ML] [Umbrella] Unify Preprocessors and Pipeline approaches to collect common statistics

[Anton Vinogradov (Jira)]

Alexey Zinoviev created IGNITE-12685:
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             Summary: [ML] [Umbrella] Unify Preprocessors  and Pipeline approaches to collect common statistics
                 Key: IGNITE-12685
                 URL: https://issues.apache.org/jira/browse/IGNITE-12685
             Project: Ignite
          Issue Type: Improvement
          Components: ml
            Reporter: Alexey Zinoviev
            Assignee: Alexey Zinoviev
             Fix For: 2.9


In the current implementation we have different behavior in Cross-Validation during running on the experimental Pipeline and chain of Preprocessors.

 

Look at the tutorial step 8 CV_Param_Grid and 8_CV_Param_Grid_and_pipeline

In the first example all preprocessors fits on the whole dataset and don't use train/test filter (due to limited API in preprocessors), and collects the stat on the whole initial dataset.

 

In the second example, we have honest re-fitting on each cross-validation fold three times with three different stats. As a result we could get a different encoding values or Max/Min values for each column and so on.

 

Should learn this question and be in consistency with the most popular approaches.

 



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