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