Description: Code to run the Non-negative Matrix Factorization algorithm as presented in the Lee, Seung 1999 Nature paper. Platform: |
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Description: 非负矩阵分解的matlab代码，内容全！希望对大家有用-Non-negative Matrix Factorization of matlab code, the contents of the whole! Hope useful for everyone Platform: |
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Description: 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 Platform: |
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