Tags: neurodata/scikit-learn
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Release v1.2.2 <!-- Thanks for contributing a pull request! Please ensure you have taken a look at the contribution guidelines: https://github.com/scikit-learn/scikit-learn/blob/main/CONTRIBUTING.md --> #### Reference Issues/PRs <!-- Example: Fixes scikit-learn#1234. See also scikit-learn#3456. Please use keywords (e.g., Fixes) to create link to the issues or pull requests you resolved, so that they will automatically be closed when your pull request is merged. See https://github.com/blog/1506-closing-issues-via-pull-requests --> #### What does this implement/fix? Explain your changes. #### Any other comments? <!-- Please be aware that we are a loose team of volunteers so patience is necessary; assistance handling other issues is very welcome. We value all user contributions, no matter how minor they are. If we are slow to review, either the pull request needs some benchmarking, tinkering, convincing, etc. or more likely the reviewers are simply busy. In either case, we ask for your understanding during the review process. For more information, see our FAQ on this topic: http://scikit-learn.org/dev/faq.html#why-is-my-pull-request-not-getting-any-attention. Thanks for contributing! --> --------- Signed-off-by: Adam Li <adam2392@gmail.com>
Refactored scikit-learn tree submodule to enable the following features: 1. separate leaf/split node setting in the Cython Tree 2. oblique splits that is the Forest-RC algorithm implemented by Breiman 2001 3. implement an abstract base class for Criterion, Splitter and Tree in Cython tree submodule 4. modularize the Python tree class to allow for different Cython tree implementations
TST use approximate equality for float comparison (scikit-learn#13749)
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