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436 – Measuring Poverty: Challenges and New Solutions
Introduction to Non-negative Matrix Factorization
George Luta
Georgetown University
Fajwel Fogel
Ecole Polytechnique ParisTech
Douglas A. Marsteller
PepsiCo
Joe Maisog
Glotech, Inc.
S. Stanley Young
National Institute of Statistical Sciences
Matrix factorization techniques are central to many statistical methods. The singular value decomposition method is often used to perform matrix factorizations although the interpretability of the elements of the factoring matrices may be problematic. We present an alternative method called non-negative matrix factorization (NMF) that has the potential to help with subject matter interpretability. The method is used when the matrix to be factored and the factoring matrices have non-negative elements. We present SAS JMP, R and Orange codes for computing NMF.