public abstract class LDAModel
extends Object
Latent Dirichlet Allocation (LDA) model.
This abstraction permits for different underlying representations, including local and distributed data structures.
Modifier and Type  Method and Description 

scala.Tuple2<int[],double[]>[] 
describeTopics()
Return the topics described by weighted terms.

abstract scala.Tuple2<int[],double[]>[] 
describeTopics(int maxTermsPerTopic)
Return the topics described by weighted terms.

abstract int 
k()
Number of topics

abstract Matrix 
topicsMatrix()
Inferred topics, where each topic is represented by a distribution over terms.

abstract int 
vocabSize()
Vocabulary size (number of terms or terms in the vocabulary)

public abstract int k()
public abstract int vocabSize()
public abstract Matrix topicsMatrix()
public abstract scala.Tuple2<int[],double[]>[] describeTopics(int maxTermsPerTopic)
This limits the number of terms per topic. This is approximate; it may not return exactly the topweighted terms for each topic. To get a more precise set of top terms, increase maxTermsPerTopic.
maxTermsPerTopic
 Maximum number of terms to collect for each topic.public scala.Tuple2<int[],double[]>[] describeTopics()
WARNING: If vocabSize and k are large, this can return a large object!