Marinka Zitnik and Blaz Zupan (2012) NIMFA: A Python Library for Nonnegative Matrix Factorization. Journal of Machine Learning Research, 13 . pp. 849-853.
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|
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