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https://api.github.com/repos/scikit-learn/scikit-learn/issues/33158 | https://api.github.com/repos/scikit-learn/scikit-learn | https://api.github.com/repos/scikit-learn/scikit-learn/issues/33158/labels{/name} | https://api.github.com/repos/scikit-learn/scikit-learn/issues/33158/comments | https://api.github.com/repos/scikit-learn/scikit-learn/issues/33158/events | https://github.com/scikit-learn/scikit-learn/issues/33158 | 3,874,821,024 | I_kwDOAAzd1s7m9ROg | 33,158 | RFC: `DecisionTree*`/`ExtraTree*`: why accepting a `splitter` parameter? (let's deprecate it) | {
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I think it's confusing to expose this parameter in the public API, I think `DecisionTree*`s should always use the "best-splitter" and `ExtraTree*` should always use the r... | null | {
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https://api.github.com/repos/scikit-learn/scikit-learn/issues/33155 | https://api.github.com/repos/scikit-learn/scikit-learn | https://api.github.com/repos/scikit-learn/scikit-learn/issues/33155/labels{/name} | https://api.github.com/repos/scikit-learn/scikit-learn/issues/33155/comments | https://api.github.com/repos/scikit-learn/scikit-learn/issues/33155/events | https://github.com/scikit-learn/scikit-learn/pull/33155 | 3,870,126,563 | PR_kwDOAAzd1s7AGjQQ | 33,155 | CI Migrate pylatest_conda_forge_mkl build to GHA | {
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✅ In particular following the pull request checklist will increase the likelihood
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} | ### Describe the bug and give evidence about its user-facing impact
Describe the bug and give evidence about its user-facing impact In sklearn/utils/estimator_checks.py, the function _yield_classifier_checks yields check_class_weight_balanced_linear_classifier twice for linear classifiers that support the class_weight... | {
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- test_multi_class_n_jobs[kernel3] | null | {
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Problems detected by ruf... | {
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#### Reference Issues/PRs
RFC #33158
#### What does this implement/fix? Explain your changes.
The `splitter` parameter (and hence `self.splitter`) can never be a `Splitter` instance, because of the parameter constraint: `"splitter": [StrOptions({... | null | {
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This PR fixes a false negative in `check_estimator`, specifically in `check_requires_y_none`, for estimators that validate `y` using the `validate_params` decorator with an `array-like` constraint.
When `y=None`, `validate_params` raises an error of the form:
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Tested it on my fork https://github.com/lesteve/scikit-learn/actions/runs/21432189253 with `workflow_dispatch` and this works fi... | {
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Fixes compatibility issue with check_requires_y_none when using @validate_params decorator.
What does this implement/fix? Explain your changes.
This PR fixes an issue where estimators using @validate_params for y parameter validation would fail the
check_requires_y_none test, while estim... | {
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> This is a request for comment (RFC), please do not open a pull request for this issue. If you wish to contribute to scikit-learn please have a look at our [contributing doc](https://scikit-learn.org/dev/developers/contributing.html) and in particular the section [New contributors](https://scikit-learn.or... | null | {
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Fixes a few typos in `plot_confusion_matrix.py`.
#### AI usage disclosure
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I tried to explain the reasons we ask for all those requirements as @reshamas suggested. | {
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#### Reference Issues/PRs
<!--
Example: Fixes #1234. See also #3456.
Please use keywords (e.g., Fixes) to create link to th... | {
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When the estimator is a clusterer, "auto" now selects "predict" when available
(e.g. KMeans).
If the clusterer does not implement predict (e.g. DBSCAN),
DecisionBoundaryDisplay.from_estimator raises a clear and explicit error
indicating... | {
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- https://arxiv.org/abs/2207.08815
- supporting code: https://github.com/LeoGrin/tabular-benchmark
The raw CSV data is available for download here:
- https://github.com/LeoGrin/tabular-benchmark/tree/main/analyses/results
We could try to mine this dat... | null | {
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The python.org no longer mentions conda as an installation method, so maybe the pytorch conda channel is no longer maintained.
I am not sure about the usefulness of adding the nvidia channel, so let's try without.
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I maintain the scikit-learn compatible projects [fastcan](https://github.com/scikit-learn-contrib/fastcan) and use `check_estimator` to check its compatibility.
When I use `sklearn.utils.column_or_1d` to validate the argument `y` of `fit`, the error message of `None` input is accepted by `check_e... | {
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### Note
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### Note
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### Note
If the CI tasks fail, create a new branch based on this PR and add the required fixes to that branch. | {
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This PR adds a new Sphinx-Gallery example
(`examples/ensemble/plot_forest_warm_start_grid_search.py`)
demonstrating a manual grid search that leverages `warm_start=True`
for tree ensembles by progressively increasing `n_estimators`.
The example compares runtime and validat... | {
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Found this bug while working on #32193 (maybe the 3rd or 4th bug found while working on this test, really this is a good test :joy:)
Let me know if you want me to open an issue describing the bug, but for now it's described it in the next section.
#### The bug
```python
from sklea... | {
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Fixes #33093. See also #33084.
#### What does this implement/fix? Explain your changes.
It implements suggestions made here https://github.com/scikit-learn/scikit-learn/issues/33093#issuecomment-3759684206
#### AI usage disclosure
I did **not** use AI assistance.
#### Any other c... | {
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This PR addresses issue #33032 by improving the numerical stability of \LinearRegression\ specifically for \ loat32\ data, while maintaining strict consistency for \ loat64\.
### The Dual-Logic Strategy (Forest & Trees)
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1.Improving clarity of the code and comments
2.Adding a fixed random_state for reproducibility
3.Making the plot behavior more consistent with the documentation
No change to algorithmic behavior or public APIs.
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🙌 Thanks for contributing a pull request!
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Unable to find junit file. Please see link for details. | {
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- Line 80: Convert .format() to f-string in list comprehension
- Line 440: Convert .format() to f-string in error message
- Line 1468: Convert % formatting to f-string in error message
This improves code consistency and aligns with... | {
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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
✅ In particular following the pull request checklist will increase the likelihood
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So far, `response_method="auto"` does not resolve correctly (list of options as for classifiers instead of `predict`).
The approach I implemented is: using PCA, followed by DBSCAN and Logistic Regression as a final step.
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## Re-enable compressed cache for `fetch_kddcup99
### Why
The KDDCup99 cache is currently forced to be written uncompressed due to a legacy
decompression workaround. This significantly inflates disk usage for a very large
dataset. Re-enabling compression reduces storage requirements and disk I/O witho... | {
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#### AI usage disclosure
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I used AI assis... | {
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} | This is to keep track and address several things we noticed in #33015
I will address them in follow-up PRs.
- [x] check number of (distinct) `colors == n_classes` (see: https://github.com/scikit-learn/scikit-learn/pull/33015/changes#r2703156456)
- [x] use same selection mechanism for all qualitative cmaps (that have ... | null | {
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Fixes #33113
The bug was detected by the test from this PR: https://github.com/scikit-learn/scikit-learn/pull/32193/
#### What does this implement/fix? Explain your changes.
First, I considered removing the erroneous `break` (see the issue).
But then I benchmarked `_any_isnan_... | {
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The `break` [here](https://github.com/scikit-learn/scikit-learn/blob/afc095a7b17d5528d62f55f07cab39f963299c78/sklearn/tree/_utils.pyx#L85) is wrong, and in some edge cases it will prevent `_any_isnan_axis0` detecting NaNs for some features. Then because of that, the splitter won't considers splits... | {
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The time needed to`cross_validate` can have a big (x100) slow down when using parallel jobs (`n_jobs > 1`).
Note that the effect is difficult to reproduce as it happens only on the first few calls to `cross_validate`, perhaps some weird caching mechanism is at play ?
### Steps/Code to Reproduce
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✅ In particular following the pull request checklist will increase the likelihood
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Fixes #33093
The previous error message incorrectly implied that an estimator without
a `predict` method was always a regressor. This change removes that
assumption and clarifies the expected behavior.
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[January 12 build log](https://github.com/scikit-learn/scikit-learn/actions/runs/20908719794/job/60067290832)
The symptom is that it fails after a very long time (more than 45 minutes in both cases) and exits... | {
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### Note
If the CI tasks fail, create a new branch based on this PR and add the required fixes to that branch. | {
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This PR removes a redundant `from sklearn.datasets import load_iris` statement in `examples/tree/plot_iris_dtc.py`.
The function `load_iris` is already imported at the top of the file (line 23), making the second import inside the plotting section (line 33) u... | {
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This PR adds `min_cardinality` and `max_cardinality` parameters to `make_column_selector`.
Currently, `make_column_selector` allows selecting columns based on dtype or regex pattern. However, selecting columns based on the number of unique values (cardinality) is a common requirement in data preprocessing, for e... | {
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AFAIK there isn't one.
#### What does this implement/fix? Explain your changes.
This rewrites the `GaussianProcessRegressor` to use the array API.
#### AI usage disclosure
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While reviewing @AnneBeyer's #33015 PR, I thought it would be nice to be able to display the decision boundaries of a classifier along with the data points with consistent color maps (at least for classifiers, outlier detectors and regressors) instead of having to a manuall... | null | {
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Current function that checks response values of an estimator
assumes that if the estimator is not a classifier or an outlier detector, then it is a regressor.
In the latter case, if it doesn't find the `predict` function,
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#### What does this implement/fix? Explain your changes.
A few clean ups around the splitting docs and error message.
#### AI usage disclosure
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closes #32076
supersedes #32239 and #32843
#### What does this implement/fix? Explain your changes.
- turns `TargetEncoder` into a metadata router that routes `groups` to the internal splitter
- adds more input options for `cv` init param (as discussed here https://github.com/scikit-lea... | {
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### Cython issue
According to https://github.com/cython/cython/pull/7427#issuecomment-3753646484 the Cython issue is fixed in master.
I think it's actually slightly better to use the install from source rather than the Cython wheel. The Cython wheel i... | {
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Fixes #33045
#### What does this implement/fix? Explain your changes.
Mixed string and number inputs do not error for the following thresholded classification metrics:
* `accuracy_score`
* `hamming_loss`
* `zero_one_loss`
* `matthews_corrcoef`
* `confusion_matrix` - only when `la... | null | {
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} | ### Describe the bug
StratifiedGroupKFold seems to be broken (Python 3.13, scikit-learn 1.8.0) for some fairly simple grouped classification datasets, quite frequently producing empty training or test sets.
While I am aware of the many issues covering poor stratification and the workarounds suggested (https://github... | null | {
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#### What does this implement/fix? Explain your changes.
This PR aligns all the coordinate descent Cython implementations with regard to the naming of penalization strength, i.e. it reverts the renaming of 21706e36b977ee29eacfa45ada4410a67b41b86c:
- l1_reg -> alpha
- l2_reg -> beta
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The original text suggested that input arrays must be of integral dtype, but the implementation does not enforce this.
This update aligns documentation with actual behavior.
Fixes #32930
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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
✅ In particular following the pull request checklist will increase the likelihood
of having maintainers review your PR:
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```
pytest --parallel-threads 4 --iterations 10 sklearn/linear_model/tests/test_logistic.py -k 'test_logreg_l1' -vs
```
My best guess is that liblinear has some thread-safe issue with random number generation, similarly to https://github.com/sc... | {
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} | ### Describe the bug
I noticed that `benchmarks/bench_multilabel_metrics.py` is currently using `metrics.jaccard_similarity_score`. This function was deprecated and subsequently removed in **scikit-learn 0.23**. Consequently, this benchmark script fails to run on current versions of scikit-learn.
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Continuation of #29313
#### What does this implement/fix? Explain your changes.
This PR adds `_array_api.check_same_namespace` to raise an error if the array namespace used during `fit` and `predict`/`transform` do not match, and `_array_api.convert_estimator` to move the array attrib... | null | {
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I encountered a failure caused by setting a non-parameter attribute in
`__init__`. This rule is easy to violate unintentionally and not very
visible in the current developer documentation.
This PR adds a short warning near the top of the estim... | {
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```
pytest --parallel-threads 4 --iterations 10 sklearn/utils/tests/test_response.py -k test_response_values_output_shape_ -v
```
Using a `clone` fixes it. As we have seen before, the issue is that the parametri... | {
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None
#### What does this implement/fix? Explain your changes.
`inspect.signature` is known to be very slow, it is not the best function for a hot path. It was identified as a performance bottleneck in our real workload. Since the method signature cannot change while maintaining method... | null | {
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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
✅ In particular following the pull request checklist will increase the likelihood
of having maintainers review your PR:
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Many users apply scikit-learn to biological datasets such as gene expression matrices, RNA-seq counts, proteomics, and metabolomics data. These datasets usually have:
- Very high dimensionality (thousands of genes/features)
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when estimator.score returns a non-finite value.
This PR ensures such iterations are skipped without emitting warnings.
Includes a regression test for GH-32908. | {
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https://api.github.com/repos/scikit-learn/scikit-learn/issues/33057 | https://api.github.com/repos/scikit-learn/scikit-learn | https://api.github.com/repos/scikit-learn/scikit-learn/issues/33057/labels{/name} | https://api.github.com/repos/scikit-learn/scikit-learn/issues/33057/comments | https://api.github.com/repos/scikit-learn/scikit-learn/issues/33057/events | https://github.com/scikit-learn/scikit-learn/pull/33057 | 3,804,659,159 | PR_kwDOAAzd1s68t9le | 33,057 | ENH add partial_fit method to NearestCentroid classifier | {
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**Fixes #12952**
Added `partial_fit` to NearestCentroid so you can train it on data in batches.
**What it does:**
- You can now feed data to NearestCentroid bit by bit
- Updates the class centers as new data comes in
- Works like GaussianNB's partial_fit
**What I changed:**
- Added the partial_fit method... | {
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https://api.github.com/repos/scikit-learn/scikit-learn/issues/33056 | https://api.github.com/repos/scikit-learn/scikit-learn | https://api.github.com/repos/scikit-learn/scikit-learn/issues/33056/labels{/name} | https://api.github.com/repos/scikit-learn/scikit-learn/issues/33056/comments | https://api.github.com/repos/scikit-learn/scikit-learn/issues/33056/events | https://github.com/scikit-learn/scikit-learn/pull/33056 | 3,804,239,985 | PR_kwDOAAzd1s68sjrk | 33,056 | doc: add integral dtype to supervised clustering metrics docstrings | {
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Fixes #32930
What does this implement/fix? Explain your changes.
This pull request standardizes the documentation for supervised clustering metrics in sklearn/metrics/cluster/_supervised.py.
Changes made:
Added dtype=integral to the labels_true and labels_pred parameters in the docstring... | {
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https://api.github.com/repos/scikit-learn/scikit-learn/issues/33055 | https://api.github.com/repos/scikit-learn/scikit-learn | https://api.github.com/repos/scikit-learn/scikit-learn/issues/33055/labels{/name} | https://api.github.com/repos/scikit-learn/scikit-learn/issues/33055/comments | https://api.github.com/repos/scikit-learn/scikit-learn/issues/33055/events | https://github.com/scikit-learn/scikit-learn/pull/33055 | 3,804,133,717 | PR_kwDOAAzd1s68sMs3 | 33,055 | BLD Add Android support | {
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* Requires https://github.com/pypa/cibuildwheel/pull/2695
* Requires https://github.com/mesonbuild/meson-python/pull/824
* Requires https://github.com/numpy/numpy/pull/30412
* Requires... | null | {
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