Package: crassmat
Type: Package
Title: Conditional Random Sampling Sparse Matrices
Version: 0.0.6
Date: 2019-06-28
Author: Nick Kunz
Maintainer: Nick Kunz <nick.kunz@columbia.edu>
Description: 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.
License: GPL-3
Depends: svMisc
Suggests: NMF, recommenderlab
Encoding: UTF-8
RoxygenNote: 6.1.1
ByteCompile: TRUE
LazyData: TRUE
Repository: https://nickkunz.r-universe.dev
Date/Publication: 2019-12-18 02:12:42 UTC
RemoteUrl: https://github.com/nickkunz/crassmat
RemoteRef: HEAD
RemoteSha: 26cabc860045e9e179b5ad43cbdc49e3c5e60155
NeedsCompilation: no
Packaged: 2026-07-13 05:57:43 UTC; root