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Showing content from http://cran.rstudio.com/web/packages/rJava/../CirceR/../rmarkdown/../dcTensor/index.html below:

CRAN: Package dcTensor

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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