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dcTensor (version 1.3.0)

Discrete Matrix/Tensor Decomposition

Description

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 .

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Install

install.packages('dcTensor')

Monthly Downloads

282

Version

1.3.0

License

MIT + file LICENSE

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Repository

https://github.com/rikenbit/dcTensor

Maintainer

Koki Tsuyuzaki

Last Published

May 11th, 2024

Functions in dcTensor (1.3.0)

dNMTF

Discretized Non-negative Matrix Tri-Factorization Algorithms (dNMTF)

dNMF

Discretized Non-negative Matrix Factorization Algorithms (dNMF)

dNTF

Discretized Non-negative CP Decomposition Algorithms (dNTF)

dsiNMF

Discretized Simultaneous Non-negative Matrix Factorization Algorithms (dsiNMF)

toyModel

Toy model data for using dNMF, dSVD, dsiNMF, djNMF, dPLS, dNTF, and dNTD

dNTD

Discretized Non-negative Tucker Decomposition Algorithms (dNTD)

dSVD

Discretized Singular Value Decomposition (dSVD)

dPLS

Discretized Partial Least Squares (dPLS)

dcTensor-package

tools:::Rd_package_title("dcTensor")

djNMF

Discretized Joint Non-negative Matrix Factorization Algorithms (djNMF)