| #------------------------------------------------------------- |
| # |
| # 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 Poisson Nonnegative Matrix Factorization (PNMF) |
| # |
| # [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_pnmf = function(Matrix[Double] X, Integer rnk, Double eps = 10^-8, Integer maxi = 10, Boolean verbose=TRUE) |
| return (Matrix[Double] W, Matrix[Double] H) |
| { |
| #initialize W and H |
| W = rand(rows=nrow(X), cols=rnk, min=0, max=0.025); |
| H = rand(rows=rnk, cols=ncol(X), min=0, max=0.025); |
| |
| i = 0; |
| while(i < maxi) { |
| H = (H*(t(W)%*%(X/(W%*%H+eps)))) / t(colSums(W)); |
| W = (W*((X/(W%*%H+eps))%*%t(H))) / t(rowSums(H)); |
| i = i + 1; |
| if( verbose ) { |
| obj = sum(W%*%H) - sum(X*log(W%*%H+eps)); |
| print("iter=" + i + " obj=" + obj); |
| } |
| } |
| } |