[SHOW PR] Submodulev2 #44
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…ecessary refactorings to enable downstream functionality (#32) #### Reference Issues/PRs This is the most up-to-date PR branch to consolidate all proposed refactor changes that work with: - unsupervised trees - oblique trees - no performance/runtime regressions against main #### What does this implement/fix? Explain your changes. Incorporates refactors to: Internal Cython of scikit-learn's: - criterion - splitter - tree Internals of Python in scikit-learns: - python Tree Adds the basic implementation of oblique trees. The implementation of oblique trees has been tested on all sklearn's `check_estimator` testing function and has error-checking bounds for the new hyperparameter introduced, which is `feature_combinations` that defaults to ``min(1.5, n_features)``. TODO: 1. [ ] ~Add honest support for trees (splitting the data at the Python API level)~ 2. [x] Build wheels 3. [ ] ~Brainstorm unit-tests, or weekly checks to determine when our fork is out-of-date compared to upstream sklearn~ 4. [x] Revamp README for the fork #### Any other comments? [cd build] --------- Signed-off-by: Adam Li <[email protected]> Co-authored-by: Chester Huynh <[email protected]> Co-authored-by: Parth Vora <[email protected]>
#### Reference Issues/PRs Fixes README and wheel building --------- Signed-off-by: Adam Li <[email protected]>
<!-- 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 <[email protected]>
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
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1994f15 introduces a regression where the missing values are not going to the node with the most nodes. |
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
… into submodulev2
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
<!-- 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 <[email protected]>
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
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As of: 9a614f4 the categorical is a bit more complicated because the stuff in sklearn/tree/_splitter.pyx was not completed. |
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
Signed-off-by: Adam Li <[email protected]>
Merging latest changes from sklearn main #### 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 <[email protected]>
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Reference Issues/PRs
Supersedes: #42
Incorporates the latest changes in scikit-learn upstream main, where missing-value support for trees was added.
What does this implement/fix? Explain your changes.
Any other comments?