decomposition.SparsePCA()

class sklearn.decomposition.SparsePCA(n_components=None, alpha=1, ridge_alpha=0.01, max_iter=1000, tol=1e-08, method='lars', n_jobs=1

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sklearn.decomposition.sparse_encode()

sklearn.decomposition.sparse_encode(X, dictionary, gram=None, cov=None, algorithm='lasso_lars', n_nonzero_coefs=None, alpha=None

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decomposition.LatentDirichletAllocation()

class sklearn.decomposition.LatentDirichletAllocation(n_topics=10, doc_topic_prior=None, topic_word_prior=None, learning_method=None

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decomposition.MiniBatchDictionaryLearning()

class sklearn.decomposition.MiniBatchDictionaryLearning(n_components=None, alpha=1, n_iter=1000, fit_algorithm='lars'

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decomposition.DictionaryLearning()

class sklearn.decomposition.DictionaryLearning(n_components=None, alpha=1, max_iter=1000, tol=1e-08, fit_algorithm='lars'

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decomposition.TruncatedSVD()

class sklearn.decomposition.TruncatedSVD(n_components=2, algorithm='randomized', n_iter=5, random_state=None, tol=0.0)

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decomposition.NMF()

class sklearn.decomposition.NMF(n_components=None, init=None, solver='cd', tol=0.0001, max_iter=200, random_state=None, alpha=0.0, l1_ratio=0

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decomposition.IncrementalPCA()

class sklearn.decomposition.IncrementalPCA(n_components=None, whiten=False, copy=True, batch_size=None)

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