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:Florian Schwendinger [aut], Emil Hvitfeldt [aut, cre]

fastTextR_2.1.0.9000.tar.gz
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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'))

Peer review:

Bug tracker:https://github.com/emilhvitfeldt/fasttextr/issues

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

On CRAN:

13 exports 4 stars 5.79 score 2 dependencies 2 dependents 43 scripts 452 downloads

Last updated 10 months agofrom:277d1aa231. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 07 2024
R-4.5-win-x86_64OKSep 07 2024
R-4.5-linux-x86_64OKSep 07 2024
R-4.4-win-x86_64OKSep 07 2024
R-4.4-mac-x86_64OKSep 07 2024
R-4.4-mac-aarch64OKSep 07 2024
R-4.3-win-x86_64OKSep 07 2024
R-4.3-mac-x86_64OKSep 07 2024
R-4.3-mac-aarch64OKSep 07 2024

Exports:fasttextft_analogiesft_controlft_loadft_nearest_neighborsft_normalizeft_predictft_saveft_sentence_vectorsft_testft_trainft_word_vectorsft_words

Dependencies:Rcppslam

fastTextR - Cheatsheet

Rendered fromCheatsheet.Rmdusingknitr::rmarkdownon Sep 07 2024.

Last update: 2023-12-05
Started: 2022-10-30

fastTextR - Text Classification

Rendered fromText_classification.Rmdusingknitr::rmarkdownon Sep 07 2024.

Last update: 2022-10-30
Started: 2022-10-30

fastTextR - Word representations

Rendered fromWord_representations.Rmdusingknitr::rmarkdownon Sep 07 2024.

Last update: 2023-12-05
Started: 2022-10-30

Readme and manuals

Help Manual

Help pageTopics
Create a New 'FastText' Modelfasttext
Get Analogiesft_analogies
Default Control Settingsft_control
Load Modelft_load
Get Nearest Neighborsft_nearest_neighbors
Normalizeft_normalize
Write Modelft_save
Get Sentence Vectorsft_sentence_vectors
Evaluate the Modelft_test
Train a Modelft_train
Get Word Vectorsft_word_vectors
Get Wordsft_words
Predict using a Previously Trained Modelft_predict predict.supervised_model