54 lines
1.9 KiB
Python
54 lines
1.9 KiB
Python
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"""
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The :mod:`sklearn.decomposition` module includes matrix decomposition
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algorithms, including among others PCA, NMF or ICA. Most of the algorithms of
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this module can be regarded as dimensionality reduction techniques.
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"""
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# TODO: remove me in 0.24 (as well as the noqa markers) and
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# import the dict_learning func directly from the ._dict_learning
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# module instead.
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# Pre-cache the import of the deprecated module so that import
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# sklearn.decomposition.dict_learning returns the function as in
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# 0.21, instead of the module.
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# https://github.com/scikit-learn/scikit-learn/issues/15842
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import warnings
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with warnings.catch_warnings():
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warnings.simplefilter("ignore", category=FutureWarning)
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from .dict_learning import dict_learning
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from ._nmf import NMF, non_negative_factorization # noqa
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from ._pca import PCA # noqa
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from ._incremental_pca import IncrementalPCA # noqa
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from ._kernel_pca import KernelPCA # noqa
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from ._sparse_pca import SparsePCA, MiniBatchSparsePCA # noqa
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from ._truncated_svd import TruncatedSVD # noqa
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from ._fastica import FastICA, fastica # noqa
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from ._dict_learning import (dict_learning_online,
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sparse_encode, DictionaryLearning,
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MiniBatchDictionaryLearning, SparseCoder) # noqa
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from ._factor_analysis import FactorAnalysis # noqa
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from ..utils.extmath import randomized_svd # noqa
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from ._lda import LatentDirichletAllocation # noqa
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__all__ = ['DictionaryLearning',
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'FastICA',
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'IncrementalPCA',
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'KernelPCA',
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'MiniBatchDictionaryLearning',
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'MiniBatchSparsePCA',
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'NMF',
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'PCA',
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'SparseCoder',
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'SparsePCA',
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'dict_learning',
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'dict_learning_online',
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'fastica',
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'non_negative_factorization',
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'randomized_svd',
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'sparse_encode',
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'FactorAnalysis',
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'TruncatedSVD',
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'LatentDirichletAllocation']
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