Package: GMTM 0.2.1

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_0.2.1.tar.gz
GMTM_0.2.1.zip(r-4.7-x86_64)GMTM_0.2.1.zip(r-4.7-arm64)GMTM_0.2.1.zip(r-4.6-x86_64)GMTM_0.2.1.zip(r-4.6-arm64)GMTM_0.2.1.zip(r-4.5-x86_64)
GMTM_0.2.1.tgz(r-4.6-x86_64)GMTM_0.2.1.tgz(r-4.6-arm64)GMTM_0.2.1.tgz(r-4.5-x86_64)GMTM_0.2.1.tgz(r-4.5-arm64)
GMTM_0.2.1.tar.gz(r-4.7-arm64)GMTM_0.2.1.tar.gz(r-4.7-x86_64)GMTM_0.2.1.tar.gz(r-4.6-arm64)GMTM_0.2.1.tar.gz(r-4.6-x86_64)
GMTM_0.2.1.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://koheiw.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/koheiw/gmtm/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

cppopenmp

4.15 score 4 stars 8 scripts 538 downloads 7 exports 23 dependencies

Last updated from:43adaf2647. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK176
linux-devel-x86_64OK176
source / vignettesOK169
linux-release-arm64OK190
linux-release-x86_64OK184
macos-release-arm64OK232
macos-release-x86_64OK400
macos-oldrel-arm64OK170
macos-oldrel-x86_64OK460
windows-devel-arm64OK263
windows-devel-x86_64OK242
windows-release-arm64OK279
windows-release-x86_64OK203
windows-oldrel-x86_64OK220
wasm-releaseOK114

Exports:as.seedwordsgroup_matrixprobabilitytermstextmodel_gmmtextmodel_kmeanstopics

Dependencies:clifastmatchirlbaISOcodesjsonlitelatticelifecyclemagrittrMatrixproxyCquantedaRcppRcppArmadilloRcppEigenrlangRSpectrarsvdSnowballCstopwordsstringiwordvectorxml2yaml