Package: rainette 0.3.3.9000

rainette: The Reinert Method for Textual Data Clustering

An R implementation of the Reinert text clustering method. For more details about the algorithm see the included vignettes or Reinert (1990) <doi:10.1177/075910639002600103>.

Authors:Julien Barnier [aut, cre], Florian Privé [ctb]

rainette_0.3.3.9000.tar.gz
rainette_0.3.3.9000.zip(r-4.7)rainette_0.3.3.9000.zip(r-4.6)rainette_0.3.3.9000.zip(r-4.5)
rainette_0.3.3.9000.tgz(r-4.6-x86_64)rainette_0.3.3.9000.tgz(r-4.6-arm64)rainette_0.3.3.9000.tgz(r-4.5-x86_64)rainette_0.3.3.9000.tgz(r-4.5-arm64)
rainette_0.3.3.9000.tar.gz(r-4.7-arm64)rainette_0.3.3.9000.tar.gz(r-4.7-x86_64)rainette_0.3.3.9000.tar.gz(r-4.6-arm64)rainette_0.3.3.9000.tar.gz(r-4.6-x86_64)
rainette_0.3.3.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
rainette/json (API)
NEWS

# Install 'rainette' in R:
install.packages('rainette', repos = c('https://juba.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/juba/rainette/issues

Pkgdown/docs site:https://juba.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

text-analysistext-classificationcpp

7.42 score 57 stars 29 scripts 586 downloads 16 exports 82 dependencies

Last updated from:5f7c5f0c8f. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK223
linux-devel-x86_64OK218
source / vignettesOK246
linux-release-arm64OK197
linux-release-x86_64OK204
macos-release-arm64OK112
macos-release-x86_64OK210
macos-oldrel-arm64OK144
macos-oldrel-x86_64OK402
windows-develOK184
windows-releaseOK193
windows-oldrelOK187
wasm-releaseOK150

Exports:clusters_by_doc_tablecutreecutree_rainettecutree_rainette2docs_by_cluster_tableimport_corpus_iramuteqmerge_segmentsrainetterainette_explorrainette_plotrainette_statsrainette2rainette2_complete_groupsrainette2_explorrainette2_plotsplit_segments

Dependencies:base64encbslibcachemclicolorspacecommonmarkcpp11curldendextenddigestdplyrfarverfastmapfastmatchfontawesomefsgenericsggplot2ggwordcloudgluegridExtragridtextgtablehighrhtmltoolshttpuvisobandISOcodesjpegjquerylibjsonlitelabelinglaterlatticelifecyclelitedownmagrittrmarkdownMatrixmemoisemimeminiUInsyllableotelpillarpkgconfigpngprogressrpromisesproxyCpurrrquantedaquanteda.textstatsR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenrlangRSpectraS7sassscalesshinySnowballCsourcetoolsstopwordsstringistringrtibbletidyrtidyselectutf8vctrsviridisviridisLitewithrxfunxml2xtableyaml

[en] Algorithms description

Julien Barnier

Rendered fromalgorithms_en.Rmdusingknitr::rmarkdownon May 05 2026.

Last update: 2026-01-05
Started: 2022-02-17

[en] Introduction to rainette

Julien Barnier

Rendered fromintroduction_en.Rmdusingknitr::rmarkdownon May 05 2026.

Last update: 2022-02-18
Started: 2020-03-09

[fr] Description des algorithmes

Julien Barnier

Rendered fromalgorithmes.Rmdusingknitr::rmarkdownon May 05 2026.

Last update: 2026-01-05
Started: 2019-01-25

[fr] Utilisation de rainette

Julien Barnier

Rendered fromintroduction_usage.Rmdusingknitr::rmarkdownon May 05 2026.

Last update: 2026-01-05
Started: 2019-01-24

Readme and manuals

Help Manual

Help pageTopics
Split a dtm into two clusters with reinert algorithmcluster_tab
Returns the number of segment of each cluster for each source documentclusters_by_doc_table
Cut a tree into groupscutree
Cut a rainette result tree into groups of documentscutree_rainette
Cut a rainette2 result object into groups of documentscutree_rainette2
Returns, for each cluster, the number of source documents with at least n segments of this clusterdocs_by_cluster_table
Import a corpus in Iramuteq formatimport_corpus_iramuteq
Merges segments according to minimum segment sizemerge_segments
return documents indices ordered by CA first axis coordinatesorder_docs
Corpus clustering based on the Reinert method - Simple clusteringrainette
Shiny gadget for rainette clustering explorationrainette_explor
Generate a clustering description plot from a rainette resultrainette_plot
Generate cluster keyness statistics from a rainette resultrainette_stats
Corpus clustering based on the Reinert method - Double clusteringrainette2
Complete groups membership with knn classificationrainette2_complete_groups
Shiny gadget for rainette2 clustering explorationrainette2_explor
Generate a clustering description plot from a rainette2 resultrainette2_plot
Remove features from dtm of each group base don cc_test and tsjselect_features
Split a character string or corpus into segmentssplit_segments split_segments.character split_segments.Corpus split_segments.corpus split_segments.tokens
Switch documents between two groups to maximize chi-square valueswitch_docs