Marinka Zitnik and Blaz Zupan (2012) NIMFA: A Python Library for Nonnegative Matrix Factorization. Journal of Machine Learning Research, 13 . pp. 849-853.
Abstract
NIMFA is an open-source Python library that provides a unified interface to nonnegative matrix factorization algorithms. It includes implementations of state-of-the-art factorization methods, initialization approaches, and quality scoring. It supports both dense and sparse matrix representation. NIMFA's component-based implementation and hierarchical design should help the users to employ already implemented techniques or design and code new strategies for matrix factorization tasks.
| Item Type: | Article |
|---|
| Keywords: | matrix factorization, Python, library |
|---|
| Related URLs: | |
|---|
| Institution: | University of Ljubljana |
|---|
| Department: | Faculty of Computer and Information Science |
|---|
| Divisions: | Faculty of Computer and Information Science > Bioinformatics Laboratory |
|---|
| Item ID: | 1706 |
|---|
| Date Deposited: | 22 May 2012 02:40 |
|---|
| Last Modified: | 02 Dec 2013 13:32 |
|---|
| URI: | http://eprints.fri.uni-lj.si/id/eprint/1706 |
|---|
Actions (login required)
![[img]](http://eprints.fri.uni-lj.si/style/images/fileicons/application_pdf.png)
