gov.sandia.cognition.text.topic
Class LatentDirichletAllocationVectorGibbsSampler.Result

java.lang.Object
  extended by gov.sandia.cognition.util.AbstractCloneableSerializable
      extended by gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler.Result
All Implemented Interfaces:
CloneableSerializable, Serializable, Cloneable
Enclosing class:
LatentDirichletAllocationVectorGibbsSampler

public static class LatentDirichletAllocationVectorGibbsSampler.Result
extends AbstractCloneableSerializable

Represents the result of performing Latent Dirichlet Allocation.

See Also:
Serialized Form

Field Summary
protected  double[][] documentTopicProbabilities
          The document-topic probabilities, which are often called the theta model parameters.
protected  double[][] topicTermProbabilities
          The topic-term probabilities, which are the often called the phi model parameters.
 
Constructor Summary
LatentDirichletAllocationVectorGibbsSampler.Result(int topicCount, int documentCount, int termCount)
          Creates a new Result.
 
Method Summary
 int getDocumentCount()
          Gets the number of documents in the dataset.
 double[][] getDocumentTopicProbabilities()
          Gets the topic-term probabilities, which are the often called the phi model parameters.
 int getTermCount()
          Gets the number of terms in the dataset.
 int getTopicCount()
          Gets the number of topics (k) created by the topic model.
 double[][] getTopicTermProbabilities()
          Gets the document-topic probabilities, which are often called the theta model parameters.
 void setDocumentTopicProbabilities(double[][] documentTopicProbabilities)
          Sets the topic-term probabilities, which are the often called the phi model parameters.
 void setTopicTermProbabilities(double[][] topicTermProbabilities)
          Sets the document-topic probabilities, which are often called the theta model parameters.
 
Methods inherited from class gov.sandia.cognition.util.AbstractCloneableSerializable
clone
 
Methods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Field Detail

topicTermProbabilities

protected double[][] topicTermProbabilities
The topic-term probabilities, which are the often called the phi model parameters. Note that if multiple samples are taken, this will be a sum of the probabilities for the different samples until the algorithm is done and they are turned into an average.


documentTopicProbabilities

protected double[][] documentTopicProbabilities
The document-topic probabilities, which are often called the theta model parameters. Note that if multiple samples are taken, this will be a sum of the probabilities for the different samples until the algorithm is done and they are turned into an average.

Constructor Detail

LatentDirichletAllocationVectorGibbsSampler.Result

public LatentDirichletAllocationVectorGibbsSampler.Result(int topicCount,
                                                          int documentCount,
                                                          int termCount)
Creates a new Result.

Parameters:
topicCount - The number of topics.
documentCount - The number of documents.
termCount - The number of terms.
Method Detail

getTopicCount

public int getTopicCount()
Gets the number of topics (k) created by the topic model.

Returns:
The number of topics created by the topic model.

getDocumentCount

public int getDocumentCount()
Gets the number of documents in the dataset.

Returns:
The number of documents.

getTermCount

public int getTermCount()
Gets the number of terms in the dataset.

Returns:
The number of terms.

getDocumentTopicProbabilities

public double[][] getDocumentTopicProbabilities()
Gets the topic-term probabilities, which are the often called the phi model parameters.

Returns:
The topic-term probabilities.

setDocumentTopicProbabilities

public void setDocumentTopicProbabilities(double[][] documentTopicProbabilities)
Sets the topic-term probabilities, which are the often called the phi model parameters.

Parameters:
documentTopicProbabilities - The topic-term probabilities.

getTopicTermProbabilities

public double[][] getTopicTermProbabilities()
Gets the document-topic probabilities, which are often called the theta model parameters.

Returns:
The document-topic probabilities.

setTopicTermProbabilities

public void setTopicTermProbabilities(double[][] topicTermProbabilities)
Sets the document-topic probabilities, which are often called the theta model parameters.

Parameters:
topicTermProbabilities - The document-topic probabilities.