NMF

NMF# class sklearn.decomposition.NMF(n_components='auto', *, init=None, solver='cd', beta_loss='frobenius', tol=0.0001, max_iter=200, random_state=None, alpha_W=0.0, alpha_H='same', l1_ratio=0.0, verbose=0, shuffle=False)[source]# Non-Negative Matrix Factorization (NMF). Find two non-negative matrices, i.e. matrices with all non-negative elements, (W, H) whose product approximates the non-negative

[teddy-g]

Scikit-LearnのNMFの使い方説明公式ページ。Initial処理にランダム以外にNNDSVDも指定できる。fit_transformで次元削減した行列が得られて、components_に削減したFeatureが格納される。便利。