Package: fastTextR 2.1.0.9000
fastTextR: An Interface to the 'fastText' Library
An interface to the 'fastText' library <https://github.com/facebookresearch/fastText>. The package can be used for text classification and to learn word vectors. An example how to use 'fastTextR' can be found in the 'README' file.
Authors:
fastTextR_2.1.0.9000.tar.gz
fastTextR_2.1.0.9000.zip(r-4.5)fastTextR_2.1.0.9000.zip(r-4.4)fastTextR_2.1.0.9000.zip(r-4.3)
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fastTextR.pdf |fastTextR.html✨
fastTextR/json (API)
NEWS
# Install 'fastTextR' in R: |
install.packages('fastTextR', repos = c('https://emilhvitfeldt.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/emilhvitfeldt/fasttextr/issues
Last updated 12 months agofrom:277d1aa231. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 06 2024 |
R-4.5-win-x86_64 | OK | Nov 06 2024 |
R-4.5-linux-x86_64 | OK | Nov 06 2024 |
R-4.4-win-x86_64 | OK | Nov 06 2024 |
R-4.4-mac-x86_64 | OK | Nov 06 2024 |
R-4.4-mac-aarch64 | OK | Nov 06 2024 |
R-4.3-win-x86_64 | OK | Nov 06 2024 |
R-4.3-mac-x86_64 | OK | Nov 06 2024 |
R-4.3-mac-aarch64 | OK | Nov 06 2024 |
Exports:fasttextft_analogiesft_controlft_loadft_nearest_neighborsft_normalizeft_predictft_saveft_sentence_vectorsft_testft_trainft_word_vectorsft_words
fastTextR - Cheatsheet
Rendered fromCheatsheet.Rmd
usingknitr::rmarkdown
on Nov 06 2024.Last update: 2023-12-05
Started: 2022-10-30
fastTextR - Text Classification
Rendered fromText_classification.Rmd
usingknitr::rmarkdown
on Nov 06 2024.Last update: 2022-10-30
Started: 2022-10-30
fastTextR - Word representations
Rendered fromWord_representations.Rmd
usingknitr::rmarkdown
on Nov 06 2024.Last update: 2023-12-05
Started: 2022-10-30
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Create a New 'FastText' Model | fasttext |
Get Analogies | ft_analogies |
Default Control Settings | ft_control |
Load Model | ft_load |
Get Nearest Neighbors | ft_nearest_neighbors |
Normalize | ft_normalize |
Write Model | ft_save |
Get Sentence Vectors | ft_sentence_vectors |
Evaluate the Model | ft_test |
Train a Model | ft_train |
Get Word Vectors | ft_word_vectors |
Get Words | ft_words |
Predict using a Previously Trained Model | ft_predict predict.supervised_model |