Non-negative matrix factorization (NMF or NNMF), also non-negative matrix approximation is a group of algorithms in multivariate analysis and linear algebra where a matrix is factorized into (usually) two matrices and , with the property that all three matrices have no negative elements.

In mathematical optimization, the problem of non-negative least squares is a type of constrained least squares problem where the coefficients are not allowed to become negative.