├── README.md
└── nmf.js


/README.md:
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 1 | nmf.js
 2 | ======
 3 | 
 4 | Implementation of Non-negative Matrix Factorization in Javascript. This is a rather ambitious project and relies on the numeric.js library for linear algebra support. 
 5 | 
 6 | Simple usage:
 7 | 
 8 |   var maxiterations = 20;
 9 |   
10 |   var k = 2;
11 |   
12 |   var tolerance = 0.001;
13 |   
14 |   var A;
15 |   
16 |   
17 |   
18 |   A = [[1,1,0,0],
19 |        [1,1,0,0],
20 |        [0,0,1,1],
21 |        [0,0,1,1]];
22 |   
23 |   
24 |   nmf_factorized = nmf.mu(A, k, maxiterations, tolerance);
25 |   
26 |   alert(numeric.prettyPrint(nmf_factorized.W));
27 |   
28 |   alert(numeric.prettyPrint(nmf_factorized.H));
29 | 


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/nmf.js:
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 1 | "use strict";
 2 | 
 3 | // Javascript implementation of Non-negative Matrix Factorisation Algorithms
 4 | 
 5 | var nmf = (typeof exports === "undefined")?(function nmf() {}):(exports);
 6 | if(typeof global !== "undefined") { global.nmf = nmf; }
 7 | 
 8 | nmf.version = "0.8";
 9 | nmf.epsilon = 0.0001;
10 | 
11 | nmf.mu = function mu(A, k, maxiterations, tolerance)
12 | {
13 |   // Implements Lee and Seungs Multiplicative Update Algorithm
14 |   var W,H, A_dim;
15 |   var m,n,i;
16 |        
17 |   A_dim = numeric.dim(A);
18 |   m = A_dim[0];
19 |   n = A_dim[1];
20 |   
21 |   W = numeric.random([m,k]); // initialize W as random matrix
22 |   H = numeric.random([k,n]); // initialize H as random matrix
23 |     
24 |   for (i=0; i<maxiterations; i++)
25 |   {
26 |     //H = H .* (W'A) ./ (W'WH + epsilon);
27 |     H = numeric.div(numeric.mul(H,(numeric.dot(numeric.transpose(W),A))),(numeric.add(numeric.dot(numeric.dot(numeric.transpose(W),W),H),nmf.epsilon)));
28 |     //W = W .* (AH' ) ./ (WHH' + epsilon);
29 |     W = numeric.div(numeric.mul(W,numeric.dot(A,numeric.transpose(H))),(numeric.add(numeric.dot(numeric.dot(W,H),numeric.transpose(H)),nmf.epsilon)));
30 |   
31 |     var A_reconstructed = numeric.dot(W,H);
32 |     
33 |     if (nmf.calculate_reconstructionError(A,A_reconstructed) <= tolerance)
34 |     {
35 |       break;
36 |     }
37 |   }
38 |   
39 |   return {W:W,H:H};
40 | }
41 | 
42 | nmf.calculate_reconstructionError = function calculate_reconstructionError(A, A_reconstructed)
43 | {
44 |   return numeric.norm2(numeric.sub(A,A_reconstructed));
45 | }
46 | 


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