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./math/py-scikit-learn, Machine learning algorithms for Python

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Branch: CURRENT, Version: 1.6.1, Package name: py312-scikit-learn-1.6.1, Maintainer: pkgsrc-users

scikit-learn is a Python module integrating classic machine learning
algorithms in the tightly-knit scientific Python world (numpy, scipy,
matplotlib). It aims to provide simple and efficient solutions to
learning problems, accessible to everybody and reusable in various
contexts: machine-learning as a versatile tool for science and
engineering.

Required to run:
[math/lapack] [math/blas] [devel/py-setuptools] [math/py-scipy] [math/py-numpy] [devel/py-cython] [lang/gcc7] [lang/python37] [devel/py-joblib]

Required to build:
[pkgtools/cwrappers]

Master sites:

Filesize: 6902.648 KB

Version history: (Expand)

CVS history: (Expand)

2025-01-30 14:44:33 by Adam Ciarcinski | Files touched by this commit (3) Package updated
Log message: py-scikit-learn: updated to 1.6.1 1.6 https://scikit-learn.org/stable/auto\_examples/release\_highlights/plot\_release\_highlights\_1\_6\_0.html
2024-10-14 08:46:10 by Thomas Klausner | Files touched by this commit (325)
Log message: *: clean-up after python38 removal
2024-09-16 12:39:19 by Adam Ciarcinski | Files touched by this commit (3) Package updated
Log message: py-scikit-learn: updated to 1.5.2 Version 1.5.2 Changes impacting many modules - |Fix Fixed performance regression in a few Cython modules in `sklearn._loss`, `sklearn.manifold`, `sklearn.metrics` and `sklearn.utils`, which were built without OpenMP support. Changelog :mod:`sklearn.calibration` - Fix Raise error when :class:`~sklearn.model_selection.LeaveOneOut` used in `cv`, matching what would happen if `KFold(n_splits=n_samples)` was used. :mod:`sklearn.compose` - Fix Fixed :class:`compose.TransformedTargetRegressor` not to raise \ `UserWarning` if transform output is set to `pandas` or `polars`, since it isn't a transformer. :mod:`sklearn.decomposition` - Fix Increase rank defficiency threshold in the whitening step of :class:`decomposition.FastICA` with `whiten_solver="eigh"` to improve the platform-agnosticity of the estimator. :mod:`sklearn.metrics` - Fix Fix a regression in :func:`metrics.accuracy_score` and in :func:`metrics.zero_one_loss` causing an error for Array API dispatch with \ multilabel inputs. :mod:`sklearn.svm` - Fix Fixed a regression in :class:`svm.SVC` and :class:`svm.SVR` such that we \ accept
2024-08-27 00:45:44 by Thomas Klausner | Files touched by this commit (1)
Log message: py-scikit-learn: meson checks for gcc>=8, GCC_REQD it
2023-11-13 11:42:42 by Thomas Klausner | Files touched by this commit (4)
Log message: py-scikit-learn: fix build on NetBSD
2023-11-06 09:40:01 by Thomas Klausner | Files touched by this commit (1)
Log message: py-scikit-learn: revert previous Committed by accident.
2023-11-01 19:39:36 by Adam Ciarcinski | Files touched by this commit (3) Package updated
Log message: py-scikit-learn: updated to 1.3.2 Version 1.3.2 ============= **October 2023** Changelog --------- :mod:`sklearn.datasets` ....................... - |Fix All dataset fetchers now accept `data_home` as any object that implements the :class:`os.PathLike` interface, for instance, :class:`pathlib.Path`. :pr:`27468` by :user:`Yao Xiao `. :mod:`sklearn.decomposition` ............................ - Fix Fixes a bug in :class:`decomposition.KernelPCA` by forcing the output of the internal :class:`preprocessing.KernelCenterer` to be a default array. When the arpack solver is used, it expects an array with a `dtype` attribute. :pr:`27583` by :user:`Guillaume Lemaitre `. :mod:`sklearn.metrics` ...................... - Fix Fixes a bug for metrics using `zero_division=np.nan` (e.g. :func:`~metrics.precision_score`) within a paralell loop (e.g. :func:`~model_selection.cross_val_score`) where the singleton for `np.nan` will be different in the sub-processes. :pr:`27573` by :user:`Guillaume Lemaitre `. :mod:`sklearn.tree` ................... - Fix Do not leak data via non-initialized memory in decision tree pickle \ files and make the generation of those files deterministic. :pr:`27580` by :user:`Loïc \ Estève `.
2023-09-27 12:57:33 by Adam Ciarcinski | Files touched by this commit (2) Package updated
Log message: py-scikit-learn: updated to 1.3.1 Version 1.3.1 ============= Changed models -------------- The following estimators and functions, when fit with the same data and parameters, may produce different models from the previous version. This often occurs due to changes in the modelling logic (bug fixes or enhancements), or in random sampling procedures. - |Fix Ridge models with `solver='sparse_cg'` may have slightly different results with scipy>=1.12, because of an underlying change in the scipy solver Changes impacting all modules ----------------------------- - Fix The `set_output` API correctly works with list input. Changelog --------- :mod:`sklearn.calibration` .......................... - Fix :class:`calibration.CalibratedClassifierCV` can now handle models that produce large prediction scores. Before it was numerically unstable. :mod:`sklearn.cluster` ...................... - Fix :class:`cluster.BisectingKMeans` could crash when predicting on data with a different scale than the data used to fit the model. - Fix :class:`cluster.BisectingKMeans` now works with data that has a single \ feature. :mod:`sklearn.cross_decomposition` .................................. - Fix :class:`cross_decomposition.PLSRegression` now automatically ravels the \ output of `predict` if fitted with one dimensional `y`. :mod:`sklearn.ensemble` ....................... - Fix Fix a bug in :class:`ensemble.AdaBoostClassifier` with \ `algorithm="SAMME"` where the decision function of each weak learner should be symmetric (i.e. the sum of the scores should sum to zero for a sample). :mod:`sklearn.feature_selection` ................................ - Fix :func:`feature_selection.mutual_info_regression` now correctly computes the result when `X` is of integer dtype. :mod:`sklearn.impute` ..................... - Fix :class:`impute.KNNImputer` now correctly adds a missing indicator column in ``transform`` when ``add_indicator`` is set to ``True`` and missing values are \ observed during ``fit``. :mod:`sklearn.metrics` ...................... - Fix