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https://issues.apache.org/jira/browse/IGNITE-9461?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Yury Babak updated IGNITE-9461:
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    Fix Version/s: 2.8

> Implement random subspace method and provide an option to combine it with 
> bagging
> ---------------------------------------------------------------------------------
>
>                 Key: IGNITE-9461
>                 URL: https://issues.apache.org/jira/browse/IGNITE-9461
>             Project: Ignite
>          Issue Type: Task
>          Components: ml
>    Affects Versions: 2.6
>            Reporter: Oleg Ignatenko
>            Priority: Major
>             Fix For: 2.8
>
>
> Implement random subspace method (aka attribute bagging or feature bagging) 
> to give ML API users more options to address overfitting. Also provide an 
> option to combine this method with bagging.
> References:
> * [Wikipedia article|https://en.wikipedia.org/wiki/Random_subspace_method] 
> {quote}Informally, this causes individual learners to not over-focus on 
> features that appear highly predictive/descriptive in the training set, but 
> fail to be as predictive for points outside that set. For this reason, random 
> subspaces are an attractive choice for problems where the number of features 
> is much larger than the number of training points, such as learning from fMRI 
> data or gene expression data...{quote}
> * [Combining Bagging and Random Subspaces to Create Better 
> Ensembles|https://pdfs.semanticscholar.org/d38f/979ad85d59fc93058279010efc73a24a712c.pdf]
> * [Bagging and the Random Subspace Method for Redundant Feature 
> Spaces|https://link.springer.com/chapter/10.1007/3-540-48219-9_1]



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