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ENH add partial_fit for DecisionTreeClassifier #50
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Commits on Mar 29, 2023
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[EXAMPLE DIFF] (Tree featuresv2) Fork of sklearn that maintains all n…
…ecessary refactorings to enable downstream functionality (scikit-learn#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 [ ] ~Brainstorm unit-tests, or weekly checks to determine when our fork is out-of-date compared to upstream sklearn~ 4.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 <adam2392@gmail.com> Co-authored-by: Chester Huynh <chester.huynh924@gmail.com> Co-authored-by: Parth Vora <pvora4@jhu.edu>
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#### Reference Issues/PRs Fixes README and wheel building --------- Signed-off-by: Adam Li <adam2392@gmail.com>
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<!-- 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>
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Successful merge with the missing value support
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[ENH] Adding leaf node samples to be stored when "quantile" tree is t…
…urned on (scikit-learn#45) #### Reference Issues/PRs Addresses the quantile-trees part of: neurodata/treeple#29 #### What does this implement/fix? Explain your changes. 1. Stores for each leaf node a 2D numpy array of the y-samples (remember `y` is (n_samples, n_outputs)) 2. Does this all the way in Criterion 3. Only supports supervised tree/splitter/criterion 4. merges in `main` 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>
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Merge branch 'submodulev2' of https://github.com/neurodata/scikit-learn…
… into submodulev2
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Fix the predict quantiles docstring
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Fix the predict quantiles docstring
Signed-off-by: Adam Li <adam2392@gmail.com>
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Merging main, but with two test failures
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Added doc to store_leaf_values
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Merge branch 'submodulev2' of https://github.com/neurodata/scikit-learn…
… into submodulev2
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Bring in monotonicity (scikit-learn#47)
<!-- 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>
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Commits on Aug 10, 2023
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ENH optimize efficiency & FIX correct param order
Co-Authored-By: Adam Li <3460267+adam2392@users.noreply.github.com>
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Commits on Aug 11, 2023
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[MERGE] Merge changes from sklearn main (scikit-learn#52)
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 <adam2392@gmail.com>
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