Package: wordmap 0.9.5
wordmap: Feature Extraction and Document Classification with Noisy Labels
Extract features and classify documents with noisy labels given by document-meta data or keyword matching Watanabe & Zhou (2020) <doi:10.1177/0894439320907027>.
Authors:
wordmap_0.9.5.tar.gz
wordmap_0.9.5.zip(r-4.7)wordmap_0.9.5.zip(r-4.6)wordmap_0.9.5.zip(r-4.5)
wordmap_0.9.5.tgz(r-4.6-any)wordmap_0.9.5.tgz(r-4.5-any)
wordmap_0.9.5.tar.gz(r-4.7-any)wordmap_0.9.5.tar.gz(r-4.6-any)
wordmap_0.9.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
wordmap/json (API)
NEWS
| # Install 'wordmap' in R: |
| install.packages('wordmap', repos = c('https://koheiw.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/koheiw/wordmap/issues
- data_corpus_ungd2017 - UN General Debate speeches from 2017
- data_dictionary_topic - Seed topic dictionary
Last updated from:b42224efa2. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 165 | ||
| source / vignettes | OK | 167 | ||
| linux-release-x86_64 | OK | 163 | ||
| macos-release-arm64 | OK | 133 | ||
| macos-oldrel-arm64 | OK | 146 | ||
| windows-devel | OK | 115 | ||
| windows-release | OK | 132 | ||
| windows-oldrel | OK | 124 | ||
| wasm-release | OK | 106 |
Exports:accuracyafeas.coefficients_textmodelas.statistics_textmodelas.summary.textmodeltextmodel_wordmaptextplot_terms
Dependencies:clicpp11farverfastmatchggplot2ggrepelgluegtableisobandISOcodesjsonlitelabelinglatticelifecyclemagrittrMatrixquantedaR6RColorBrewerRcpprlangS7scalesSnowballCstopwordsstringivctrsviridisLitewithrxml2yaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Evaluate classification accuracy in precision and recall | accuracy summary.textmodel_wordmap_accuracy |
| Compute Average Feature Entropy (AFE) | afe |
| Create lexicon from a Wordmap model | as.dictionary.textmodel_wordmap as.list.textmodel_wordmap |
| Extract coefficients from a Wordmap model | coef.textmodel_wordmap coefficients.textmodel_wordmap |
| UN General Debate speeches from 2017 | data_corpus_ungd2017 |
| Seed topic dictionary | data_dictionary_topic |
| Predict the most likely class of documents | predict.textmodel_wordmap |
| A model for multinomial feature extraction and document classification | textmodel_wordmap |
| Plot coefficients of words | textplot_terms |
