NMF-DTU-Toolbox

代码说明：

  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)

文件列表：

NMF-DTU-Toolbox
...............\compare.m,761,2014-11-11
...............\email.zip,3206651,2015-04-01
...............\IndianPines.mat,5716968,2015-03-30
...............\nmf.m,2610,2014-11-11
...............\nmf_als.asv,1482,2015-05-07
...............\nmf_als.m,1481,2014-11-11
...............\nmf_alsobs.m,3234,2014-11-11
...............\nmf_cjlin.m,3968,2014-11-11
...............\nmf_euclidean_dist.m,60,2014-11-11
...............\nmf_mm.m,1861,2014-11-11
...............\nmf_prob.m,1749,2014-11-11
...............\order_comp.m,243,2014-11-11
...............\petAnalyzeImage.zip,6527353,2015-04-01
...............\READ ME.txt,6194,2015-04-01
...............\sina_live_setup20130528.exe,311224,2015-04-05
...............\test_toolbox.m,522,2015-04-02