| #------------------------------------------------------------- |
| # |
| # Licensed to the Apache Software Foundation (ASF) under one |
| # or more contributor license agreements. See the NOTICE file |
| # distributed with this work for additional information |
| # regarding copyright ownership. The ASF licenses this file |
| # to you under the Apache License, Version 2.0 (the |
| # "License"); you may not use this file except in compliance |
| # with the License. You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, |
| # software distributed under the License is distributed on an |
| # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| # KIND, either express or implied. See the License for the |
| # specific language governing permissions and limitations |
| # under the License. |
| # |
| #------------------------------------------------------------- |
| |
| # Implements Gaussian Nonnegative Matrix Factorization (GNMF) |
| # |
| # [Chao Liu, Hung-chih Yang, Jinliang Fan, Li-Wei He, Yi-Min Wang: |
| # Distributed nonnegative matrix factorization for web-scale dyadic |
| # data analysis on mapreduce. WWW 2010: 681-690] |
| |
| m_gnmf = function(Matrix[Double] X, Integer rnk, Double eps = 10^-8, Integer maxi = 10) |
| return (Matrix[Double] W, Matrix[Double] H) |
| { |
| #initialize W and H |
| W = rand(rows=nrow(X), cols=rnk, min=-0.05, max=0.05); |
| H = rand(rows=rnk, cols=ncol(X), min=-0.05, max=0.05); |
| |
| i = 0; |
| while(i < maxi) { |
| H = H * ((t(W) %*% X) / (((t(W) %*% W) %*% H)+eps)); |
| W = W * ((X %*% t(H)) / ((W %*% (H %*% t(H)))+eps)); |
| i = i + 1; |
| } |
| } |