swift-lda: Online sampler for Latent Dirichlet Allocation
Online Gibbs sampler for Latent Dirichlet Allocation. LDA is a generative admixture model frequently used for topic modeling and other applications. The primary goal of this implementation is to be used for probabilistic soft word class induction. The sampler can be used in an online as well as batch mode. This package uses an imperative implementation in the ST monad.
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| Versions [RSS] | 0.4.0, 0.4.1, 0.7.0.0 |
|---|---|
| Dependencies | array (>=0.3), base (>=3 && <5), containers (>=0.4), ghc-prim (>=0.2), mwc-random (>=0.12), primitive (>=0.4), vector (>=0.9) [details] |
| License | BSD-3-Clause |
| Author | Grzegorz Chrupała <pitekus@gmail.com> |
| Maintainer | Grzegorz Chrupała <pitekus@gmail.com> |
| Category | Natural Language Processing |
| Home page | https://bitbucket.org/gchrupala/colada |
| Uploaded | by GrzegorzChrupala at 2014-03-26T08:49:29Z |
| Distributions | |
| Reverse Dependencies | 2 direct, 0 indirect [details] |
| Downloads | 2377 total (11 in the last 30 days) |
| Rating | (no votes yet) [estimated by Bayesian average] |
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| Status | Docs available [build log] Successful builds reported [all 1 reports] |