[Track v1.4] New PR branch to serve as submodule for scikit-tree #53
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❌ Linting issuesThis PR is introducing linting issues. Here's a summary of the issues. Note that you can avoid having linting issues by enabling You can see the details of the linting issues under the
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adam2392
commented
Aug 24, 2023
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PSSF23
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Aug 25, 2023
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I cannot reproduce the error on my local machine with following code:
from sklearn.ensemble import RandomForestClassifier
import numpy as np
from inspect import signature
rnd = np.random.RandomState(0)
n_samples = 30
X = rnd.uniform(size=(n_samples, 3))
y = np.arange(n_samples)
clf_1 = RandomForestClassifier()
clf_1.set_params(random_state=0)
func = getattr(clf_1, "fit", None)
func(X,y)
args = [p.name for p in signature(func).parameters.values()]
func = getattr(clf_1, "score", None)
func(X,y)
args = [p.name for p in signature(func).parameters.values()]
func = getattr(clf_1, "partial_fit", None)
func(X,y)
args = [p.name for p in signature(func).parameters.values()]The code should replicate most of the check_fit_score_takes_y test, but it runs smoothly every time. I also don't understand why only these 2 CIs failed when all should have the same test library.
- Linux_Runs pylatest_conda_forge_mkl
- macOS pylatest_conda_mkl_no_openmp
If you try running the |
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@adam2392 Is |
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Yeah it should be. The test is commented out tho rn. |
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adam2392
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Signed-off-by: Adam Li <adam2392@gmail.com>
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TODO: Change
see: https://github.com/scikit-learn/scikit-learn/pull/27352/files and related PRs |
Signed-off-by: Adam Li <adam2392@gmail.com>
This was accomplished in 9a5d91b |
Signed-off-by: Adam Li <adam2392@gmail.com>
Signed-off-by: Adam Li <adam2392@gmail.com>
Signed-off-by: Adam Li <adam2392@gmail.com>
Signed-off-by: Adam Li <adam2392@gmail.com>
Signed-off-by: Adam Li <adam2392@gmail.com>
Signed-off-by: Adam Li <adam2392@gmail.com>
Signed-off-by: Adam Li <adam2392@gmail.com>
Signed-off-by: Adam Li <adam2392@gmail.com>
Signed-off-by: Adam Li <adam2392@gmail.com>
Signed-off-by: Adam Li <adam2392@gmail.com>
Signed-off-by: Adam Li <adam2392@gmail.com>
Signed-off-by: Adam Li <adam2392@gmail.com>
Signed-off-by: Adam Li <adam2392@gmail.com>
Signed-off-by: Adam Li <adam2392@gmail.com>
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We should remove binning for now as it is a untested feature... |
Signed-off-by: Adam Li <adam2392@gmail.com>
Signed-off-by: Adam Li <adam2392@gmail.com>
Signed-off-by: Adam Li <adam2392@gmail.com>
Signed-off-by: Adam Li <adam2392@gmail.com>
Signed-off-by: Adam Li <adam2392@gmail.com>
Signed-off-by: Adam Li <adam2392@gmail.com>
Signed-off-by: Adam Li <adam2392@gmail.com>
<!-- 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 neurodata/treeple#339 <!-- 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: https://scikit-learn.org/dev/faq.html#why-is-my-pull-request-not-getting-any-attention. Thanks for contributing! -->
According to errors in neurodata/treeple#361, `xfail_checks` is not available in the tags.
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Reference Issues/PRs
As of v0.2 for sktree, we have decided we do not need a custom built and released via pypi scikit-learn fork. Instead, we just have to keep an updated fork branch here that maintains the changes under
tree/andensemble/.This branch has significantly lower diff and less complexity compared to e.g. #44
What does this implement/fix? Explain your changes.
Any other comments?