""" 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, MiniBatchNMF, 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", "MiniBatchNMF", "MiniBatchSparsePCA", "NMF", "PCA", "SparseCoder", "SparsePCA", "dict_learning", "dict_learning_online", "fastica", "non_negative_factorization", "randomized_svd", "sparse_encode", "FactorAnalysis", "TruncatedSVD", "LatentDirichletAllocation", ]