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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:

Please use the canonical form https://CRAN.R-project.org/package=dcTensor to link to this page.

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.