说明：  matlab源代码，是非负矩阵分解工具箱，包含乘法更新，最小二乘约束，投影梯度法等方法
(Usage: [W,H] = nmf(X,K,alg,maxiter,speak) W: output matrix H: output matrix X: input matrix K: number of components alg: algorithm to use maxiter: maximum number of iterations speak: print to screen Algorithms: mm: Multiplicative updates method using euclidean distance measure. cjlin: Projected gradient method prob: Probabilistic non-negative matrix factorization. als: Alternating least squares. alsobs: Alternating least squares with optimal brain surgeon. Demonstrations: PET: NMF on a PET dataset Text: NMF used on a three different datasets Email, medical, and CNN. Algorithms mm: Multiplicative update method using euclidean distance measure. Described in Lee and Seung, 2001, Algorithms for Non-negative Matrix Factorization, Advances in Neural Information Processing Systems 13, 556-562. This algorithm is the most commonly used algorithm to solve NMF. cjlin: Alternative non-negative least squares using projected gradients. Author: Chih-Je)