Uses of Class
org.knowceans.dirichlet.lda.LdaGibbsSampler

Packages that use LdaGibbsSampler

org.knowceans.dirichlet.atm
org.knowceans.dirichlet.lda
org.knowceans.dirichlet.sandbox
org.knowceans.sandbox.hlda
org.knowceans.sandbox.ilda

Uses of LdaGibbsSampler in org.knowceans.dirichlet.atm

Subclasses of LdaGibbsSampler in org.knowceans.dirichlet.atm

class	AtmGibbsQuerySampler AtmGibbsQuerySampler allows sampling from known markov states, i.e., the model of an author-corpus, which can be used to predict the topics of query documents.
class	AtmGibbsSampler Gibbs sampler for estimating the best assignments of topics for words and authors of documents in a corpus.

Uses of LdaGibbsSampler in org.knowceans.dirichlet.lda

Subclasses of LdaGibbsSampler in org.knowceans.dirichlet.lda

class

LdaGibbsQuerySampler LdaGibbsQuerySampler allows sampling from known markov states, i.e., the model of a corpus, which can be used to predict the topics of query documents.

Constructors in org.knowceans.dirichlet.lda with parameters of type LdaGibbsSampler

LdaTopicSimilarities(LdaGibbsSampler lda, boolean terms, boolean docs, boolean pl, boolean js)
Initialise topic similarities using an existing lda gibbs sampler, whose phi and theta values are shared.

Uses of LdaGibbsSampler in org.knowceans.dirichlet.sandbox

Subclasses of LdaGibbsSampler in org.knowceans.dirichlet.sandbox

class

LdaGibbsSamplerHyper Gibbs sampler for estimating the best assignments of topics for words and documents in a corpus.

Uses of LdaGibbsSampler in org.knowceans.sandbox.hlda

Subclasses of LdaGibbsSampler in org.knowceans.sandbox.hlda

class

HldaGibbsSampler Gibbs sampler for estimating the best assignments of topics for words and documents in a corpus, using a hierarchical approach with a Chinese restaurant process prior.

Uses of LdaGibbsSampler in org.knowceans.sandbox.ilda

Subclasses of LdaGibbsSampler in org.knowceans.sandbox.ilda

class

IldaGibbsSampler Gibbs sampler for estimating the best assignments of topics for words and documents in a corpus.