hankcs/LDA4j sits at 196 stars on GitHub, written primarily in Java. A Java implemention of LDA(Latent Dirichlet Allocation)
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A Java implemention of LDA(Latent Dirichlet Allocation). Inference topics from a set of documents with few lines of Java code.
How To Use
code
public static void main(String[] args)
{
// 1. Load corpus from disk
Corpus corpus = Corpus.load("data/mini");
// 2. Create a LDA sampler
LdaGibbsSampler ldaGibbsSampler = new LdaGibbsSampler(corpus.getDocument(), corpus.getVocabularySize());
// 3. Train it
ldaGibbsSampler.gibbs(10);
// 4. The phi matrix is a LDA model, you can use LdaUtil to explain it.
double[][] phi = ldaGibbsSampler.getPhi();
Map<String, Double>[] topicMap = LdaUtil.translate(phi, corpus.getVocabulary(), 10);
LdaUtil.explain(topicMap);
}
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How active is development on hankcs/LDA4j?
The most recent commit recorded on hankcs/LDA4j was 9.6 years ago, based on the GitHub push timestamp. The repository has 139 forks — one of the better signals of community interest.
How many stars does hankcs/LDA4j have?
hankcs/LDA4j has 196 GitHub stars — refresh the page for the live number, or check github.com/hankcs/LDA4j. TopGit mirrors GitHub's count but does not claim minute-by-minute accuracy.
What is hankcs/LDA4j?
hankcs/LDA4j (hankcs/LDA4j) is a Java project on GitHub. From the project's own README: A Java implemention of LDA(Latent Dirichlet Allocation)
What language is hankcs/LDA4j written in?
hankcs/LDA4j is written primarily in Java. GitHub's language field is based on the largest share of bytes in the default branch.
Read full README in the tab above.
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