"""
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.
"""


from ._nmf import NMF, non_negative_factorization
from ._pca import PCA
from ._incremental_pca import IncrementalPCA
from ._kernel_pca import KernelPCA
from ._sparse_pca import SparsePCA, MiniBatchSparsePCA
from ._truncated_svd import TruncatedSVD
from ._fastica import FastICA, fastica
from ._dict_learning import (dict_learning, dict_learning_online,
                             sparse_encode, DictionaryLearning,
                             MiniBatchDictionaryLearning, SparseCoder)
from ._factor_analysis import FactorAnalysis
from ..utils.extmath import randomized_svd
from ._lda import LatentDirichletAllocation


__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']
