SPIDER The Spider Objects

NMF object


   A=nmf(H) returns a Non-negative Matrix Factorization object.
   Given matrix X>0   creates matrices W,H>0 with X ~ X*=W*H
   Usage:  [r n]=train(nmf,data(abs(rand(nrofsamples,nroffeatures))));
   Result: r.X = approximated X*  , r.Y= original X
    implementation for the MPG journal club. faster code available from the seungs lab.
  
   
    Hyperparameters, and their defaults
  
     N=5; 	            -- number of final basis functions
     maxIteration=50;    -- maximum number of iterations per cycle
     nrofrestarts=5;     -- nr of restarts to overcome local minima.
     
    Model
  
     W  =            new coordinates of object.
     H  =            new basis vectors.
   
    Methods:
  
     train 
     testing 
    Example:
     d=data(rand(20,10));
     [r,n]=train(nmf('N=2'),d);

Reference : Algorithms for Non-negative Matrix Factorization
Author : Daniel D. Lee, H. Sebastian Seung
Link : http://citeseer.ist.psu.edu/lee00algorithms.html