
    {Kg                         d Z ddlmZ ddlmZmZmZmZmZm	Z	 ddl
mZ ddlmZmZ ddlmZ ddlmZ dd	lmZ dd
lmZmZmZ ddlmZ ddlmZmZ ddlmZ g dZ y)zMatrix decomposition algorithms.

These include PCA, NMF, ICA, and more. Most of the algorithms of this module can be
regarded as dimensionality reduction techniques.
   )randomized_svd   )DictionaryLearningMiniBatchDictionaryLearningSparseCoderdict_learningdict_learning_onlinesparse_encode)FactorAnalysis)FastICAfastica)IncrementalPCA)	KernelPCA)LatentDirichletAllocation)NMFMiniBatchNMFnon_negative_factorization)PCA)MiniBatchSparsePCA	SparsePCA)TruncatedSVD)r   r   r   r   r   r   r   r   r   r   r   r   r	   r   r   r   r
   r   r   r   N)!__doc__utils.extmathr   _dict_learningr   r   r   r   r	   r
   _factor_analysisr   _fasticar   r   _incremental_pcar   _kernel_pcar   _ldar   _nmfr   r   r   _pcar   _sparse_pcar   r   _truncated_svdr   __all__     b/home/alanp/www/video.onchill/myenv/lib/python3.12/site-packages/sklearn/decomposition/__init__.py<module>r(      sF    +  - & , " + 
  6 (r&   