Oleg Ignatenko created IGNITE-9461:
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Summary: 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
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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