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A word embeddings-based semi-supervised model for document scaling Watanabe (2020) <doi:10.1080/19312458.2020.1832976>. LSS allows users to analyze large and complex corpora on arbitrary dimensions with seed words exploiting efficiency of word embeddings (SVD, Glove). It can generate word vectors on a users-provided corpus or incorporate a pre-trained word vectors.
Version: | 1.4.0 |
Depends: | methods, R (≥ 3.5.0) |
Imports: | quanteda (≥ 2.0), quanteda.textstats, stringi, digest, Matrix, RSpectra, irlba, rsvd, rsparse, proxyC, stats, ggplot2, ggrepel, reshape2, locfit |
Suggests: | knitr, rmarkdown, testthat |
Published: | 2024-03-05 |
DOI: | 10.32614/CRAN.package.LSX |
Author: | Kohei Watanabe [aut, cre, cph] |
Maintainer: | Kohei Watanabe <watanabe.kohei at gmail.com> |
BugReports: | https://github.com/koheiw/LSX/issues |
License: | GPL-3 |
URL: | https://koheiw.github.io/LSX/ |
NeedsCompilation: | no |
Materials: | NEWS |
CRAN checks: | LSX results |
Reference manual: | LSX.pdf |
Package source: | LSX_1.4.0.tar.gz |
Windows binaries: | r-devel: LSX_1.4.0.zip, r-release: LSX_1.4.0.zip, r-oldrel: LSX_1.4.0.zip |
macOS binaries: | r-release (arm64): LSX_1.4.0.tgz, r-oldrel (arm64): LSX_1.4.0.tgz, r-release (x86_64): LSX_1.4.0.tgz, r-oldrel (x86_64): LSX_1.4.0.tgz |
Old sources: | LSX archive |
Please use the canonical form https://CRAN.R-project.org/package=LSX to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.