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Conducts conditional random sampling on observed values in sparse matrices. Useful for training and test set splitting sparse matrices prior to model fitting in cross-validation procedures and estimating the predictive accuracy of data imputation methods, such as matrix factorization or singular value decomposition (SVD). Although designed for applications with sparse matrices, CRASSMAT can also be applied to complete matrices, as well as to those containing missing values.
| Version: | 0.0.6 |
| Depends: | svMisc |
| Suggests: | NMF, recommenderlab |
| Published: | 2019-07-02 |
| DOI: | 10.32614/CRAN.package.crassmat |
| Author: | Nick Kunz |
| Maintainer: | Nick Kunz <nick.kunz at columbia.edu> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | crassmat results |
| Reference manual: | crassmat.pdf |
| Package source: | crassmat_0.0.6.tar.gz |
| Windows binaries: | r-devel: crassmat_0.0.6.zip, r-release: crassmat_0.0.6.zip, r-oldrel: crassmat_0.0.6.zip |
| macOS binaries: | r-release (arm64): crassmat_0.0.6.tgz, r-oldrel (arm64): crassmat_0.0.6.tgz, r-release (x86_64): crassmat_0.0.6.tgz, r-oldrel (x86_64): crassmat_0.0.6.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.