ptf: Probit Tensor Factorization

Efficient algorithms to implement Probit Tensor Factorization (PTF) model for statistical relational learning, which not only inherits the computation efficiency from the classic tensor factorization model but also accounts for the binary nature of relational data. The methodology is based on Ye Liu (2021) <https://repository.lib.ncsu.edu/bitstream/handle/1840.20/37507/etd.pdf?sequence=1> "Computational Methods for Complex Models with Latent Structure".

Version: 0.0.1
Imports: Rcpp (≥ 0.12.9), Matrix (≥ 1.2), rARPACK (≥ 0.11), plyr (≥ 1.8.4)
LinkingTo: Rcpp, RcppArmadillo
Published: 2021-06-15
Author: Ye Liu
Maintainer: Ye Liu <yliu87 at ncsu.edu>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: yes
CRAN checks: ptf results

Downloads:

Reference manual: ptf.pdf
Package source: ptf_0.0.1.tar.gz
Windows binaries: r-devel: ptf_0.0.1.zip, r-devel-UCRT: ptf_0.0.1.zip, r-release: ptf_0.0.1.zip, r-oldrel: ptf_0.0.1.zip
macOS binaries: r-release (arm64): ptf_0.0.1.tgz, r-release (x86_64): ptf_0.0.1.tgz, r-oldrel: ptf_0.0.1.tgz

Linking:

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