Nothing
lda.svi: Fit Latent Dirichlet Allocation Models using Stochastic Variational Inference
Fits Latent Dirichlet Allocation topic models to text data using the stochastic variational inference algorithm described in Hoffman et. al. (2013) <arXiv:1206.7051v3>. This method is more efficient than the original batch variational inference algorithm for LDA, and allows users to fit LDA models with more topics and to larger text corpora than would be feasible using that older method.
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Nicholas Erskine [aut, cre] |
| Maintainer | Nicholas Erskine <nicholas.erskine95@gmail.com> |
| License | MIT + file LICENSE |
| Version | 0.1.0 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the lda.svi package in your browser
Any scripts or data that you put into this service are public.
