Non-negative matrix factorization - Wikipedia

Illustration of approximate non-negative matrix factorization: the matrix V is represented by the two smaller matrices W and H, which, when multiplied, approximately reconstruct V. Non-negative matrix factorization (NMF or NNMF), also non-negative matrix approximation[1][2] is a group of algorithms in multivariate analysis and linear algebra where a matrix V is factorized into (usually) two matric

[Rion778]

非負値行列因子分解

[rawwell]

the fact that data can be recreated as a linear combination of the set of resolved "basis" data is advantageous in some lines of study. One such use is for collaborative filtering in recommendation systems where it is advantageous to know not only how much two individuals are alike, which can be der