Python modules for machine learning and data mining
scikits.learn is a python module for machine learning built on top of scipy.
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Filename | Size | Changed |
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_link | 0000000154 154 Bytes | |
_multibuild | 0000000123 123 Bytes | |
python-scikit-learn.changes | 0000096659 94.4 KB | |
python-scikit-learn.spec | 0000005225 5.1 KB | |
scikit_learn-1.5.0.tar.gz | 0007820839 7.46 MB |
Revision 67 (latest revision is 78)
Daniel Garcia (dgarcia)
committed
(revision 67)
- Update to 1.5.0 (bsc#1226185, CVE-2024-5206): ## Security * Fix feature_extraction.text.CountVectorizer and feature_extraction.text.TfidfVectorizer no longer store discarded tokens from the training set in their stop_words_ attribute. This attribute would hold too frequent (above max_df) but also too rare tokens (below min_df). This fixes a potential security issue (data leak) if the discarded rare tokens hold sensitive information from the training set without the model developer’s knowledge. ## Changed models * Efficiency The subsampling in preprocessing.QuantileTransformer is now more efficient for dense arrays but the fitted quantiles and the results of transform may be slightly different than before (keeping the same statistical properties). #27344 by Xuefeng Xu. * Enhancement decomposition.PCA, decomposition.SparsePCA and decomposition.TruncatedSVD now set the sign of the components_ attribute based on the component values instead of using the transformed data as reference. This change is needed to be able to offer consistent component signs across all PCA solvers, including the new svd_solver="covariance_eigh" option introduced in this release. ## Changes impacting many modules * Fix Raise ValueError with an informative error message when passing 1D sparse arrays to methods that expect 2D sparse inputs. #28988 by Olivier Grisel. * API Change The name of the input of the inverse_transform method of estimators has been standardized to X. As a consequence, Xt is deprecated and will be removed in version 1.7 in the following estimators: cluster.FeatureAgglomeration, decomposition.MiniBatchNMF, decomposition.NMF,
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