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. © 2012 Marinka Žitnik and Blaž Zupan.
CITATION STYLE
Žitnik, M., & Zupan, B. (2012). NIMFA: A python library for nonnegative matrix factorization. Journal of Machine Learning Research, 13, 849–853.
Mendeley helps you to discover research relevant for your work.