52 lines
1.3 KiB
Python
52 lines
1.3 KiB
Python
"""
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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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from ..utils.extmath import randomized_svd
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from ._dict_learning import (
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DictionaryLearning,
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MiniBatchDictionaryLearning,
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SparseCoder,
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dict_learning,
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dict_learning_online,
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sparse_encode,
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)
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from ._factor_analysis import FactorAnalysis
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from ._fastica import FastICA, fastica
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from ._incremental_pca import IncrementalPCA
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from ._kernel_pca import KernelPCA
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from ._lda import LatentDirichletAllocation
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from ._nmf import (
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NMF,
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MiniBatchNMF,
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non_negative_factorization,
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)
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from ._pca import PCA
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from ._sparse_pca import MiniBatchSparsePCA, SparsePCA
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from ._truncated_svd import TruncatedSVD
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__all__ = [
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"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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"MiniBatchNMF",
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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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]
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