41 lines
1.4 KiB
Python
41 lines
1.4 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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from .nmf import NMF, non_negative_factorization
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from .pca import PCA, RandomizedPCA
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from .incremental_pca import IncrementalPCA
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from .kernel_pca import KernelPCA
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from .sparse_pca import SparsePCA, MiniBatchSparsePCA
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from .truncated_svd import TruncatedSVD
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from .fastica_ import FastICA, fastica
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from .dict_learning import (dict_learning, dict_learning_online, sparse_encode,
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DictionaryLearning, MiniBatchDictionaryLearning,
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SparseCoder)
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from .factor_analysis import FactorAnalysis
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from ..utils.extmath import randomized_svd
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from .online_lda import LatentDirichletAllocation
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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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'RandomizedPCA',
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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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