[DRAFT] Allowing trees to bin data #25
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Fixed link to Jake Vanderplas website.
* Doc fix link for random projections * Doc fix link for random projections
Co-authored-by: Loïc Estève <loic.esteve@ymail.com>
Update reference link to "A survey of Partial Least Squares (PLS) methods, with emphasis on the two-block case" by JA Wegelin
…t-learn#23658) Co-authored-by: Loïc Estève <loic.esteve@ymail.com>
Co-authored-by: Loïc Estève <loic.esteve@ymail.com>
…c functions (scikit-learn#23514) Co-authored-by: Julien Jerphanion <git@jjerphan.xyz>
Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org> Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com> Co-authored-by: Julien Jerphanion <git@jjerphan.xyz>
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Mar 28, 2023
#### Reference Issues/PRs Closes: #25 Closes: #23 #### What does this implement/fix? Explain your changes. Adds preliminary capability for binning features. The cons is we need to "bin" again during predict time. I've documented how we can get around this in the README, but it will involve some heavy-duty Cython coding. - Remove Oblique tree models and migrated to scikit-tree - Fix up CI so that way unnecessary workflows are not ran on the fork - Updated the documentation with the current limitation of binning --------- Signed-off-by: Adam Li <adam2392@gmail.com>
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Reference Issues/PRs
Fixes: #23
What does this implement/fix? Explain your changes.
This aims to implement the binning capabilities to massively improves the speed of training decision trees. Currently, this is trying to add the binning capabilities that play well with the existing codebase.
Unfortunately, the code from #24 is far from complete and does not do the job.
Right now, what is missing is:
Any other comments?