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https://issues.apache.org/jira/browse/IGNITE-10955?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16754883#comment-16754883
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Artem Malykh commented on IGNITE-10955:
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Current implementation of boosting appears to be more readable in the state as
it is currently implemented. The problem with migration is that training in
boosting is sequential while models composition is parallel with weighted
aggregator. It is possible to extend sequential trainer composition to output
some general composition with specification of this composition producer, but
for me it seems more cumbersome than it is currently implemented in GDB. But
work that has been done related to this feature and that maybe be helpful in
future is extracted into a separate ticket (IGNITE-111222).
> [ML] Migrate boosting implementation to sequential trainers composition
> combinator
> ----------------------------------------------------------------------------------
>
> Key: IGNITE-10955
> URL: https://issues.apache.org/jira/browse/IGNITE-10955
> Project: Ignite
> Issue Type: Improvement
> Components: ml
> Affects Versions: 2.8
> Reporter: Artem Malykh
> Assignee: Artem Malykh
> Priority: Major
>
> There are two trainers composition primitives which are used in other
> ensemble training methods (Bagging and Stacking) implementation. To unify
> implementation I suggest to rewrite impl of boosting using these composition
> primitives as well.
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