dcTensor: Discrete Matrix/Tensor Decomposition

Semi-Binary and Semi-Ternary Matrix Decomposition are performed based on Non-negative Matrix Factorization (NMF) and Singular Value Decomposition (SVD). For the details of the methods, see the reference section of GitHub README.md <https://github.com/rikenbit/dcTensor>.

Version:	1.3.0
Depends:	R (≥ 3.4.0)
Imports:	methods, MASS, fields, rTensor, nnTensor
Suggests:	knitr, rmarkdown, testthat
Published:	2024-05-11
DOI:	10.32614/CRAN.package.dcTensor
Author:	Koki Tsuyuzaki [aut, cre]
Maintainer:	Koki Tsuyuzaki <k.t.the-answer at hotmail.co.jp>
License:	MIT + file LICENSE
URL:	https://github.com/rikenbit/dcTensor
NeedsCompilation:	no
Materials:	NEWS
CRAN checks:	dcTensor results

Documentation:

Reference manual:

dcTensor.pdf

Vignettes:

1. Discretized Non-negative Matrix Factorization ('dNMF') 2. Discretized Non-negative Tri-Matrix Factorization ('dNMTF') 2. Discretized Singular Value Decomposition ('dSVD') 3. Discretized Simultaneous Non-negative Matrix Factrozation ('dsiNMF') 4. Discretized Joint Non-negative Matrix Factrozation ('djNMF') 5. Discretized Partial Least Squares ('dPLS') 6. Discretized Non-negative Tensor Factorization ('dNTF') 7. Discretized Non-negative Tucker Decomposition ('dNTD')

Downloads:

Package source:	dcTensor_1.3.0.tar.gz
Windows binaries:	r-devel: dcTensor_1.3.0.zip, r-release: dcTensor_1.3.0.zip, r-oldrel: dcTensor_1.3.0.zip
macOS binaries:	r-release (arm64): dcTensor_1.3.0.tgz, r-oldrel (arm64): dcTensor_1.3.0.tgz, r-release (x86_64): dcTensor_1.3.0.tgz, r-oldrel (x86_64): dcTensor_1.3.0.tgz
Old sources:	dcTensor archive

Linking:

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