content: """
  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']
  