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

["Alexey Zinoviev (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/IGNITE-12685?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Alexey Zinoviev updated IGNITE-12685:
-------------------------------------
    Fix Version/s:     (was: 2.9)
                   2.10

> [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
>            Priority: Major
>             Fix For: 2.10
>
>
> 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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