NIMFA: A Python Library for Nonnegative Matrix Factorization

نویسندگان

  • Marinka Zitnik
  • Blaz Zupan
چکیده

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.

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عنوان ژورنال:
  • Journal of Machine Learning Research

دوره 13  شماره 

صفحات  -

تاریخ انتشار 2012