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"""Matrix decomposition algorithms.
These include PCA, NMF, ICA, and more. Most of the algorithms of this module can be
regarded as dimensionality reduction techniques.
"""
# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause
from ..utils.extmath import randomized_svd
from ._dict_learning import (
DictionaryLearning,
MiniBatchDictionaryLearning,
SparseCoder,
dict_learning,
dict_learning_online,
sparse_encode,
)
from ._factor_analysis import FactorAnalysis
from ._fastica import FastICA, fastica
from ._incremental_pca import IncrementalPCA
from ._kernel_pca import KernelPCA
from ._lda import LatentDirichletAllocation
from ._nmf import (
NMF,
MiniBatchNMF,
non_negative_factorization,
)
from ._pca import PCA
from ._sparse_pca import MiniBatchSparsePCA, SparsePCA
from ._truncated_svd import TruncatedSVD
__all__ = [
"NMF",
"PCA",
"DictionaryLearning",
"FactorAnalysis",
"FastICA",
"IncrementalPCA",
"KernelPCA",
"LatentDirichletAllocation",
"MiniBatchDictionaryLearning",
"MiniBatchNMF",
"MiniBatchSparsePCA",
"SparseCoder",
"SparsePCA",
"TruncatedSVD",
"dict_learning",
"dict_learning_online",
"fastica",
"non_negative_factorization",
"randomized_svd",
"sparse_encode",
]
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