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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