Package: tensorBF 1.0.2

tensorBF: Bayesian Tensor Factorization

Bayesian Tensor Factorization for decomposition of tensor data sets using the trilinear CANDECOMP/PARAFAC (CP) factorization, with automatic component selection. The complete data analysis pipeline is provided, including functions and recommendations for data normalization and model definition, as well as missing value prediction and model visualization. The method performs factorization for three-way tensor datasets and the inference is implemented with Gibbs sampling.

Authors:Suleiman A Khan [aut, cre], Muhammad Ammad-ud-din [aut]

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NEWS

# Install 'tensorBF' in R:
install.packages('tensorBF', repos = c('https://suleimank.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 1 stars 9 scripts 150 downloads 1 mentions 9 exports 1 dependencies

Last updated 6 years agofrom:bf051a0197. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 31 2024
R-4.5-winOKOct 31 2024
R-4.5-linuxOKOct 31 2024
R-4.4-winOKOct 31 2024
R-4.4-macOKOct 31 2024
R-4.3-winOKOct 31 2024
R-4.3-macOKOct 31 2024

Exports:getDefaultOptsnormFiberCenteringnormSlabScalingplotTensorBFpredictTensorBFreconstructTensorBFtensorBFundoFiberCenteringundoSlabScaling

Dependencies:tensor