NIMFA : A Python Library for Nonnegative Matrix Factorization
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.
Cite
Text
Žitnik and Zupan. "NIMFA : A Python Library for Nonnegative Matrix Factorization." Machine Learning Open Source Software, 2012.Markdown
[Žitnik and Zupan. "NIMFA : A Python Library for Nonnegative Matrix Factorization." Machine Learning Open Source Software, 2012.](https://mlanthology.org/mloss/2012/zitnik2012jmlr-nimfa/)BibTeX
@article{zitnik2012jmlr-nimfa,
title = {{NIMFA : A Python Library for Nonnegative Matrix Factorization}},
author = {Žitnik, Marinka and Zupan, Blaž},
journal = {Machine Learning Open Source Software},
year = {2012},
pages = {849-853},
volume = {13},
url = {https://mlanthology.org/mloss/2012/zitnik2012jmlr-nimfa/}
}