[
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.
>
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
