Package: GMTM 0.2.0

Kohei Watanabe

GMTM: Gaussian Mixture Topic Models

Gaussian mixture models (GMM) and k-means for topic analysis of dense document vectors. The underlying clustering functions rely on the Armadillo library (Sanderson & Curtin, 2017) <doi:10.1109/ICSPCS.2017.8270510>.

Authors:Kohei Watanabe [aut, cre, cph], Sanderson Conrad [ctb, cph], Curtin Ryan [ctb, cph]

GMTM_0.2.0.tar.gz
GMTM_0.2.0.zip(r-4.7-x86_64)GMTM_0.2.0.zip(r-4.7-arm64)GMTM_0.2.0.zip(r-4.6-x86_64)GMTM_0.2.0.zip(r-4.6-arm64)
GMTM_0.2.0.tar.gz(r-4.7-arm64)GMTM_0.2.0.tar.gz(r-4.7-x86_64)GMTM_0.2.0.tar.gz(r-4.6-arm64)GMTM_0.2.0.tar.gz(r-4.6-x86_64)
GMTM_0.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
GMTM/json (API)

# Install 'GMTM' in R:
install.packages('GMTM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

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

cppopenmp

1.30 score 8 scripts 547 downloads 7 exports 23 dependencies

Last updated from:9c8fdedb6d. Checks:10 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK186
linux-devel-x86_64OK180
source / vignettesOK229
linux-release-arm64OK154
linux-release-x86_64OK172
windows-devel-arm64OK266
windows-devel-x86_64OK210
windows-release-arm64OK249
windows-release-x86_64OK183
wasm-releaseOK116

Exports:as.seedwordsgroup_matrixprobabilitytermstextmodel_gmmtextmodel_kmeanstopics

Dependencies:clifastmatchirlbaISOcodesjsonlitelatticelifecyclemagrittrMatrixproxyCquantedaRcppRcppArmadilloRcppEigenrlangRSpectrarsvdSnowballCstopwordsstringiwordvectorxml2yaml