fastTopics

Implements fast, scalable optimization algorithms for fitting topic models ("grade of membership" models) and non-negative matrix factorizations to count data. The methods exploit the special relationship between the multinomial topic model (also, "probabilistic latent semantic indexing") and Poisson non-negative matrix factorization. The package provides tools to compare, annotate and visualize model fits, including functions to efficiently create "structure plots" and identify key features in topics. The 'fastTopics' package is a successor to the 'CountClust' package. For more information, see doi:10.48550/arXiv.2105.13440 and doi:10.1186/s13059-023-03067-9. Please also see the GitHub repository for additional vignettes not included in the package on CRAN.

Last 30 days

This package has been downloaded 331 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 21 times.

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Last 365 days

This package has been downloaded 4,391 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Jul 23, 2024 with 60 downloads.

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