dcTensor
1.3.1Discrete Matrix/Tensor Decomposition
Overview
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.
Install
Health
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 97%
- Return-value docs
- 100%
- References docs
- 70%
Downloads
Repository
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Repository practices
3 development-tooling and community-health practices detected across 3 families in the upstream repository
Checks run against github.com/rikenbit/dctensor on 2026-08-16.
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
7 releases. Pick two to compare their code metrics. R releases are shown for context.
Package metadata
- First published
- 2023-02-21
- Total releases
- 7 / 3 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 3.4.0
- Download size
- 1.5 MB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("dcTensor")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
Cite the R Observatory
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From data release v2026-08-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.