In this paper, dimensionality reduction via matrix factorization with nonnegativity constraints is studied. Because of these constraints, it stands apart from other linear dimensionality reduction methods. Here we explore nonnegative matrix factorization in combination with a classifier for protein fold recognition. Since typically matrix factorization is iteratively done, convergence can be slow. To alleviate this problem, a significantly faster (more than 11 times) algorithm is proposed. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Okun, O., Priisalu, H., & Alves, A. (2005). Fast non-negative dimensionality reduction for protein fold recognition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3720 LNAI, pp. 665–672). https://doi.org/10.1007/11564096_67
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