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sklearn/decomposition/__init__.py
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Loïc Estève
MNT Switch to absolute imports enforced by `ruff` (#31847)
29 июл 2025, 16:42
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29 июл 2025, 16:42
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"""Matrix decomposition algorithms. These include PCA, NMF, ICA, and more. Most of the algorithms of this module can be regarded as dimensionality reduction techniques. """ # Authors: The scikit-learn developers # SPDX-License-Identifier: BSD-3-Clause from sklearn.decomposition._dict_learning import ( DictionaryLearning, MiniBatchDictionaryLearning, SparseCoder, dict_learning, dict_learning_online, sparse_encode, ) from sklearn.decomposition._factor_analysis import FactorAnalysis from sklearn.decomposition._fastica import FastICA, fastica from sklearn.decomposition._incremental_pca import IncrementalPCA from sklearn.decomposition._kernel_pca import KernelPCA from sklearn.decomposition._lda import LatentDirichletAllocation from sklearn.decomposition._nmf import NMF, MiniBatchNMF, non_negative_factorization from sklearn.decomposition._pca import PCA from sklearn.decomposition._sparse_pca import MiniBatchSparsePCA, SparsePCA from sklearn.decomposition._truncated_svd import TruncatedSVD from sklearn.utils.extmath import randomized_svd __all__ = [ "NMF", "PCA", "DictionaryLearning", "FactorAnalysis", "FastICA", "IncrementalPCA", "KernelPCA", "LatentDirichletAllocation", "MiniBatchDictionaryLearning", "MiniBatchNMF", "MiniBatchSparsePCA", "SparseCoder", "SparsePCA", "TruncatedSVD", "dict_learning", "dict_learning_online", "fastica", "non_negative_factorization", "randomized_svd", "sparse_encode", ]