Package: crassmat 0.0.6

Nick Kunz

crassmat: Conditional Random Sampling Sparse Matrices

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.

Authors:Nick Kunz

crassmat_0.0.6.tar.gz
crassmat_0.0.6.zip(r-4.7-any)crassmat_0.0.6.zip(r-4.6-any)crassmat_0.0.6.zip(r-4.5-any)
crassmat_0.0.6.tgz(r-4.6-any)crassmat_0.0.6.tgz(r-4.5-any)
crassmat_0.0.6.tar.gz(r-4.7-any)crassmat_0.0.6.tar.gz(r-4.6-any)
crassmat_0.0.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
crassmat/json (API)

# Install 'crassmat' in R:

install.packages('crassmat', repos = c('https://nickkunz.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/nickkunz/crassmat/issues

Datasets:

A - Sparse Matrix A

On CRAN:

matrix-functions matrix-library sampling-methods

2.70 score 1 stars 266 downloads 1 exports 3 dependencies

Last updated from:26cabc8600. Checks:7 NOTE, 2 OK. Indexed: yes.

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