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NNLM: Fast and Versatile Non-Negative Matrix Factorization
This is a package for Non-Negative Linear Models (NNLM). It implements fast sequential coordinate descent algorithms for non-negative linear regression and non-negative matrix factorization (NMF). It supports mean square error and Kullback-Leibler divergence loss. Many other features are also implemented, including missing value imputation, domain knowledge integration, designable W and H matrices and multiple forms of regularizations.
Getting started
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Package details |
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| Author | Xihui Lin [aut, cre], Paul C Boutros [aut] |
| Maintainer | Xihui Lin <ericxihuilin@outlook.com> |
| License | BSD_2_clause + file LICENSE |
| Version | 0.4.3 |
| URL | https://github.com/linxihui/NNLM |
| Package repository | View on CRAN |
| Installation |
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