Package: tidylda 0.0.6.999
tidylda: Latent Dirichlet Allocation Using 'tidyverse' Conventions
Implements an algorithm for Latent Dirichlet Allocation (LDA), Blei et at. (2003) <https://www.jmlr.org/papers/volume3/blei03a/blei03a.pdf>, using style conventions from the 'tidyverse', Wickham et al. (2019)<doi:10.21105/joss.01686>, and 'tidymodels', Kuhn et al.<https://tidymodels.github.io/model-implementation-principles/>. Fitting is done via collapsed Gibbs sampling. Also implements several novel features for LDA such as guided models and transfer learning.
Authors:
tidylda_0.0.6.999.tar.gz
tidylda_0.0.6.999.zip(r-4.5)tidylda_0.0.6.999.zip(r-4.4)tidylda_0.0.6.999.zip(r-4.3)
tidylda_0.0.6.999.tgz(r-4.4-x86_64)tidylda_0.0.6.999.tgz(r-4.4-arm64)tidylda_0.0.6.999.tgz(r-4.3-x86_64)tidylda_0.0.6.999.tgz(r-4.3-arm64)
tidylda_0.0.6.999.tar.gz(r-4.5-noble)tidylda_0.0.6.999.tar.gz(r-4.4-noble)
tidylda_0.0.6.999.tgz(r-4.4-emscripten)tidylda_0.0.6.999.tgz(r-4.3-emscripten)
tidylda.pdf |tidylda.html✨
tidylda/json (API)
NEWS
| # Install 'tidylda' in R: |
| install.packages('tidylda', repos = c('https://tommyjones.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/tommyjones/tidylda/issues
- nih_sample - Abstracts and metadata from NIH research grants awarded in 2014
- nih_sample_dtm - Abstracts and metadata from NIH research grants awarded in 2014
Last updated 3 months agofrom:03a86e3359. Checks:OK: 9. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 23 2024 |
| R-4.5-win-x86_64 | OK | Oct 23 2024 |
| R-4.5-linux-x86_64 | OK | Oct 23 2024 |
| R-4.4-win-x86_64 | OK | Oct 23 2024 |
| R-4.4-mac-x86_64 | OK | Oct 23 2024 |
| R-4.4-mac-aarch64 | OK | Oct 23 2024 |
| R-4.3-win-x86_64 | OK | Oct 23 2024 |
| R-4.3-mac-x86_64 | OK | Oct 23 2024 |
| R-4.3-mac-aarch64 | OK | Oct 23 2024 |
Exports:augmentcalc_prob_coherenceglanceposteriorrefittidytidylda
Dependencies:clicpp11dplyrfansigenericsgluegtoolsjaneaustenrlatticelifecyclemagrittrMatrixmvrsquaredpillarpkgconfigpurrrR6RcppRcppArmadilloRcppProgressRcppThreadrlangSnowballCstringistringrtibbletidyrtidyselecttidytexttokenizersutf8vctrswithr
Introduction to tidylda
Rendered fromtidylda-intro.Rmdusingknitr::rmarkdownon Oct 23 2024.Last update: 2024-07-03
Started: 2022-11-26
Probabilistic Coherence
Rendered fromprobabilistic-coherence.Rmdusingknitr::rmarkdownon Oct 23 2024.Last update: 2023-07-14
Started: 2022-11-26
Transfer Learning with LDA (tLDA)
Rendered fromtLDA.Rmdusingknitr::rmarkdownon Oct 23 2024.Last update: 2024-07-03
Started: 2022-11-26
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Augment method for 'tidylda' objects | augment.tidylda |
| Probabilistic coherence of topics | calc_prob_coherence |
| Glance method for 'tidylda' objects | glance.tidylda |
| Abstracts and metadata from NIH research grants awarded in 2014 | nih nih_sample nih_sample_dtm |
| Draw from the marginal posteriors of a tidylda topic model | posterior posterior.tidylda |
| Get predictions from a Latent Dirichlet Allocation model | predict.tidylda |
| Print Method for tidylda | print.tidylda |
| Update a Latent Dirichlet Allocation topic model | refit.tidylda |
| Tidy a matrix from a 'tidylda' topic model | tidy.matrix tidy.tidylda |
| Fit a Latent Dirichlet Allocation topic model | tidylda |
