有没有好的库可以快速进行非负矩阵分解(NMF)?

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问题描述

我有一个形状为 570000 * 3000 的稀疏矩阵.我尝试 nima 进行NMF(使用默认的nmf方法，并将max_iter设置为65).但是，我发现nimfa非常慢.有没有人使用更快的库来做NMF?

I have a sparse matrix whose shape is 570000*3000. I tried nima to do NMF (using the default nmf method, and set max_iter to 65). However, I found nimfa very slow. Have anyone used a faster library to do NMF?

推荐答案

我使用了之前.它是用C编写的，非常快. 论文记录了算法和代码

I have used libNMF before. It's written in C and is very fast. There is a paper documenting the algorithm and code.

本文还列出了NMF的几种替代软件包(以多种不同的语言(我已在此处复制以供将来参考).

The paper also lists several alternative packages for NMF (in bunch of different languages (which I have copied here for future reference).

Mathworks [3，33]
- Matlab
- http://www.mathworks.com/access/helpdesk/help/toolbox/stats/nnmf .
- The Mathworks [3, 33]
  - Matlab
  - http://www.mathworks.com/access/helpdesk/help/toolbox/stats/nnmf.
  - Matlab
  - http://www.cmpe.boun.edu.tr/~cemgil/bnmf
  - Matlab
  - http://www.bsp.brain.riken.jp/ICALAB/nmflab .
  - Matlab
  - http://eu.wiley.com/WileyCDA/WileyTitle/productCd- 0470746661.html
  - Matlab
  - http://isp.imm.dtu.dk/toolbox/nmf/index.html
  - Matlab
  - http://www.cs.helsinki.fi/u/phoyer/software.html
  - Matlab
  - http://userweb.cs.utexas. edu/users/dmkim/Source/software/nnma/index.html
  - Matlab/Python
  - http://www.csie.ntu.edu.tw/~cjlin/nmf/index.html
  - Matlab
  - http://mikkelschmidt.dk/index.php?id=2
  - R
  - http://cran.r-project.org/web/packages/NMF/index.html
  - R
  - http://cran.r-project.org/web/packages/NMFN/index.html
  - Python
  - http://www.eecs.berkeley.edu/~ericb
  - Python
  - http://www.procoders.net/?p=409
  - C ++
  - http://www.kyb.mpg. de/bs/people/suvrit/work/progs/nnma.html
  - C ++
  - http://mlg.ucd.ie/nmf
  - C ++
  - http://www.insight-journal.org/browse/publication/152
  - C ++
  - http://www.biomedcentral.com/1471-2105/7/175
  免责声明:除了MATLAB之外，我没有尝试过其他任何软件包.
  Disclaimer: I have not tried any of these other packages (aside from MATLAB's).
  
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