Package: LDAShiny 0.9.3
LDAShiny: User-Friendly Interface for Review of Scientific Literature
Contains the development of a tool that provides a web-based graphical user interface (GUI) to perform a review of the scientific literature under the Bayesian approach of Latent Dirichlet Allocation (LDA)and machine learning algorithms. The application methodology is framed by the well known procedures in topic modelling on how to clean and process data. Contains methods described by Blei, David M., Andrew Y. Ng, and Michael I. Jordan (2003) <https://jmlr.org/papers/volume3/blei03a/blei03a.pdf> Allocation"; Thomas L. Griffiths and Mark Steyvers (2004) <doi:10.1073/pnas.0307752101> ; Xiong Hui, et al (2019) <doi:10.1016/j.cie.2019.06.010>.
Authors:
LDAShiny_0.9.3.tar.gz
LDAShiny_0.9.3.zip(r-4.5)LDAShiny_0.9.3.zip(r-4.4)LDAShiny_0.9.3.zip(r-4.3)
LDAShiny_0.9.3.tgz(r-4.4-any)LDAShiny_0.9.3.tgz(r-4.3-any)
LDAShiny_0.9.3.tar.gz(r-4.5-noble)LDAShiny_0.9.3.tar.gz(r-4.4-noble)
LDAShiny_0.9.3.tgz(r-4.4-emscripten)LDAShiny_0.9.3.tgz(r-4.3-emscripten)
LDAShiny.pdf |LDAShiny.html✨
LDAShiny/json (API)
| # Install 'LDAShiny' in R: |
| install.packages('LDAShiny', repos = c('https://javierdelahoz.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/javierdelahoz/ldashiny/issues
- crude - 20 Exemplary News Articles from the Reuters-21578 Data Set of Topic crude
Last updated 4 years agofrom:204cfe108f. Checks:OK: 1 NOTE: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 27 2024 |
| R-4.5-win | NOTE | Oct 27 2024 |
| R-4.5-linux | NOTE | Oct 27 2024 |
| R-4.4-win | NOTE | Oct 27 2024 |
| R-4.4-mac | NOTE | Oct 27 2024 |
| R-4.3-win | NOTE | Oct 27 2024 |
| R-4.3-mac | NOTE | Oct 27 2024 |
Exports:removeSparseTermsrunLDAShiny
Dependencies:askpassassertthataudiobackportsbase64encbeeprBHbroombslibcachemchinese.miscclicolorspacecommonmarkcpp11crayoncrosstalkcurldata.tabledigestdplyrDTevaluatefansifarverfastmapfastmatchfloatfontawesomefsgenericsggplot2gluegmpgtablegtoolshighcharterhighrhtmltoolshtmlwidgetshttpuvhttrigraphisobandISOcodesjaneaustenrjiebaRjiebaRDjquerylibjsonliteknitrlabelinglaterlatticelazyevalldatuninglgrlifecyclelubridatemagrittrMASSMatrixMatrixExtramemoisemgcvmimemlapimodeltoolsmunsellnlmeNLPopensslpillarpkgconfigplotlyplyrpromisespurrrquantedaquantmodR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenRcppProgressreshape2RhpcBLASctlrjsonrlangrlistrmarkdownRmpfrrsparseRSpectrasassscalesshinyshinyalertshinyBSshinycssloadersshinydashboardshinyjsshinyWidgetsslamSnowballCsourcetoolsstopwordsstringistringrsystext2vectextmineRtibbletidyrtidyselecttidytexttimechangetinytextmtokenizerstopicmodelsTTRutf8uuidvctrsviridisLitewithrxfunXMLxml2xtablextsyamlzoo
A brief introduction to LDAShiny
Rendered fromA_brief_introduction_to_LDAShiny.Rmdusingknitr::rmarkdownon Oct 27 2024.Last update: 2021-01-30
Started: 2021-01-22
Una breve introducción a LDAShiny
Rendered fromUna_breve_introducci-n_a_LDAShiny.Rmdusingknitr::rmarkdownon Oct 27 2024.Last update: 2021-01-30
Started: 2021-01-22
