ProbabilisticLatentSemanticAnalysis (Cognitive Foundry)

java.lang.Object
- gov.sandia.cognition.util.AbstractCloneableSerializable
- - gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm
  - - gov.sandia.cognition.algorithm.AbstractAnytimeAlgorithm<ResultType>
    - - gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner<java.util.Collection<? extends Vectorizable>,ProbabilisticLatentSemanticAnalysis.Result>
      - gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis

All Implemented Interfaces:: AnytimeAlgorithm<ProbabilisticLatentSemanticAnalysis.Result>, IterativeAlgorithm, StoppableAlgorithm, AnytimeBatchLearner<java.util.Collection<? extends Vectorizable>,ProbabilisticLatentSemanticAnalysis.Result>, BatchLearner<java.util.Collection<? extends Vectorizable>,ProbabilisticLatentSemanticAnalysis.Result>, VectorFactoryContainer, CloneableSerializable, Randomized, java.io.Serializable, java.lang.Cloneable

@PublicationReference(author="Thomas Hofmann",title="Probabilistic Latent Semantic Analysis",year=1999,type=Conference,publication="Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence (UAI)",pages={289,296},url="http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.33.1187") @PublicationReference(author="Thomas Hofmann",title="Probabilistic Latent Semantic Indexing",year=1999,type=Conference,publication="Proceedings of the 22nd Conference of the ACM Special Interest Group on Information Retreival (SIGIR)",pages={50,57},url="http://portal.acm.org/citation.cfm?id=312649") @PublicationReference(author="Thomas Hofmann",title="Unsupervised Learning by Probabilistic Latent Semantic Analysis",year=2001,type=Journal,publication="Machine Learning",pages={177,196},url="http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.130.6341")
public class ProbabilisticLatentSemanticAnalysis
extends AbstractAnytimeBatchLearner<java.util.Collection<? extends Vectorizable>,ProbabilisticLatentSemanticAnalysis.Result>
implements Randomized, VectorFactoryContainer

An implementation of the Probabilistic Latent Semantic Analysis (PLSA) algorithm.

Since:: 3.0
Author:: Justin Basilico
See Also:: Serialized Form

Nested Class Summary

Nested Classes
Modifier and Type	Class and Description
`static class`	`ProbabilisticLatentSemanticAnalysis.LatentData` The information about each latent variable.
`static class`	`ProbabilisticLatentSemanticAnalysis.Result` The dimensionality transform created by probabilistic latent semantic analysis.
`static class`	`ProbabilisticLatentSemanticAnalysis.StatusPrinter` Prints out the status of the probabilistic latent semantic analysis algorithm.

Field Summary

Fields
Modifier and Type	Field and Description
`protected double`	`changeOfLogLikelihood` The change in log-likelihood of the algorithm from the current iteration.
`static int`	`DEFAULT_MAX_ITERATIONS` The default maximum number of iterations is 250.
`static double`	`DEFAULT_MINIMUM_CHANGE` The default minimum change is 1.0E-10.
`static int`	`DEFAULT_REQUESTED_RANK` The default requested rank is 10.
`protected int`	`documentCount` The number of documents.
`protected Matrix`	`documentsByTerms` The document-by-term matrix.
`protected int`	`latentCount` The number of latent variables.
`protected ProbabilisticLatentSemanticAnalysis.LatentData[]`	`latents` The information about each of the latent variables.
`protected double`	`logLikelihood` The current log-likelihood of the algorithm.
`protected MatrixFactory<? extends Matrix>`	`matrixFactory` The matrix factory.
`protected double`	`minimumChange` The minimum change required in log-likelihood to continue iterating.
`protected java.util.Random`	`random` The random number generator to use.
`protected int`	`requestedRank` The requested rank to reduce the dimensionality to.
`protected ProbabilisticLatentSemanticAnalysis.Result`	`result` The result being produced by the algorithm.
`protected int`	`termCount` The number of terms.
`protected VectorFactory<? extends Vector>`	`vectorFactory` The vector factory.

Fields inherited from class gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner
data, keepGoing

Fields inherited from class gov.sandia.cognition.algorithm.AbstractAnytimeAlgorithm
maxIterations

Fields inherited from class gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm
DEFAULT_ITERATION, iteration

Constructor Summary

Constructors
Constructor and Description
`ProbabilisticLatentSemanticAnalysis()` Creates a new ProbabilisticSemanticAnalysis with default parameters.
`ProbabilisticLatentSemanticAnalysis(int requestedRank)` Creates a new ProbabilisticLatentSemanticAnalysis with the given rank and otherwise default parameters.
`ProbabilisticLatentSemanticAnalysis(int requestedRank, double minimumChange, java.util.Random random)` Creates a new ProbabilisticLatentSemanticAnalysis with the given parameters.
`ProbabilisticLatentSemanticAnalysis(java.util.Random random)` Creates a new ProbabilisticLatentSemanticAnalysis with default parameters and the given random number generator.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`protected void`	`cleanupAlgorithm()` Called to clean up the learning algorithm's state after learning has finished.
`MatrixFactory<? extends Matrix>`	`getMatrixFactory()` Gets the matrix factory to use.
`double`	`getMinimumChange()` Gets the minimum change in log-likelihood to allow before stopping the algorithm.
`java.util.Random`	`getRandom()` Gets the random number generator used by this object.
`int`	`getRequestedRank()` Gets the requested rank to conduct the analysis for.
`ProbabilisticLatentSemanticAnalysis.Result`	`getResult()` Gets the current result of the algorithm.
`VectorFactory<? extends Vector>`	`getVectorFactory()` Gets the vector factory to use.
`protected boolean`	`initializeAlgorithm()` Called to initialize the learning algorithm's state based on the data that is stored in the data field.
`void`	`setMatrixFactory(MatrixFactory<? extends Matrix> matrixFactory)` Sets the matrix factory to use.
`void`	`setMinimumChange(double minimumChange)` Sets the minimum change in log-likelihood to allow before stopping the algorithm.
`void`	`setRandom(java.util.Random random)` Sets the random number generator used by this object.
`void`	`setRequestedRank(int requestedRank)` Sets the requested rank to conduct the analysis for.
`void`	`setVectorFactory(VectorFactory<? extends Vector> vectorFactory)` Sets the vector factory to use.
`protected boolean`	`step()` Called to take a single step of the learning algorithm.

Methods inherited from class gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner
clone, getData, getKeepGoing, learn, setData, setKeepGoing, stop

Methods inherited from class gov.sandia.cognition.algorithm.AbstractAnytimeAlgorithm
getMaxIterations, isResultValid, setMaxIterations

Methods inherited from class gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm
addIterativeAlgorithmListener, fireAlgorithmEnded, fireAlgorithmStarted, fireStepEnded, fireStepStarted, getIteration, getListeners, removeIterativeAlgorithmListener, setIteration, setListeners

Methods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface gov.sandia.cognition.algorithm.AnytimeAlgorithm
getMaxIterations, setMaxIterations

Methods inherited from interface gov.sandia.cognition.algorithm.IterativeAlgorithm
addIterativeAlgorithmListener, getIteration, removeIterativeAlgorithmListener

Methods inherited from interface gov.sandia.cognition.algorithm.StoppableAlgorithm
isResultValid

- Field Detail
  - DEFAULT_REQUESTED_RANK
```
public static final int DEFAULT_REQUESTED_RANK
```
    The default requested rank is 10.
    
    See Also:
    
    Constant Field Values
  - DEFAULT_MAX_ITERATIONS
```
public static final int DEFAULT_MAX_ITERATIONS
```
    The default maximum number of iterations is 250.
    
    See Also:
    
    Constant Field Values
  - DEFAULT_MINIMUM_CHANGE
```
public static final double DEFAULT_MINIMUM_CHANGE
```
    The default minimum change is 1.0E-10.
    
    See Also:
    
    Constant Field Values
  - requestedRank
```
protected int requestedRank
```
    The requested rank to reduce the dimensionality to.
  - minimumChange
```
protected double minimumChange
```
    The minimum change required in log-likelihood to continue iterating. Used for a stopping criteria.
  - random
```
protected java.util.Random random
```
    The random number generator to use.
  - vectorFactory
```
protected VectorFactory<? extends Vector> vectorFactory
```
    The vector factory.
  - matrixFactory
```
protected MatrixFactory<? extends Matrix> matrixFactory
```
    The matrix factory.
  - documentsByTerms
```
protected transient Matrix documentsByTerms
```
    The document-by-term matrix.
  - termCount
```
protected transient int termCount
```
    The number of terms.
  - documentCount
```
protected transient int documentCount
```
    The number of documents.
  - latentCount
```
protected transient int latentCount
```
    The number of latent variables.
  - latents
```
protected transient ProbabilisticLatentSemanticAnalysis.LatentData[] latents
```
    The information about each of the latent variables.
  - logLikelihood
```
protected transient double logLikelihood
```
    The current log-likelihood of the algorithm.
  - changeOfLogLikelihood
```
protected transient double changeOfLogLikelihood
```
    The change in log-likelihood of the algorithm from the current iteration.
  - result
```
protected transient ProbabilisticLatentSemanticAnalysis.Result result
```
    The result being produced by the algorithm.
- Constructor Detail
  - ProbabilisticLatentSemanticAnalysis
```
public ProbabilisticLatentSemanticAnalysis()
```
    Creates a new ProbabilisticSemanticAnalysis with default parameters.
  - ProbabilisticLatentSemanticAnalysis
```
public ProbabilisticLatentSemanticAnalysis(java.util.Random random)
```
    Creates a new ProbabilisticLatentSemanticAnalysis with default parameters and the given random number generator.
    
    Parameters:
    
    random - The random number generator to use.
  - ProbabilisticLatentSemanticAnalysis
```
public ProbabilisticLatentSemanticAnalysis(int requestedRank)
```
    Creates a new ProbabilisticLatentSemanticAnalysis with the given rank and otherwise default parameters.
    
    Parameters:
    
    requestedRank - The requested rank. Must be non-negative.
  - ProbabilisticLatentSemanticAnalysis
```
public ProbabilisticLatentSemanticAnalysis(int requestedRank,
                                           double minimumChange,
                                           java.util.Random random)
```
    Creates a new ProbabilisticLatentSemanticAnalysis with the given parameters.
    
    Parameters:
    
    requestedRank - The requested rank. Must be non-negative.
    
    minimumChange - The minimum change in log-likelihood to stop.
    
    random - The random number generator to use.
- Method Detail
  - initializeAlgorithm
```
protected boolean initializeAlgorithm()
```
    Description copied from class: AbstractAnytimeBatchLearner
    
    Called to initialize the learning algorithm's state based on the data that is stored in the data field. The return value indicates if the algorithm can be run or not based on the initialization.
    
    Specified by:
    
    initializeAlgorithm in class AbstractAnytimeBatchLearner<java.util.Collection<? extends Vectorizable>,ProbabilisticLatentSemanticAnalysis.Result>
    
    Returns:
    
    True if the learning algorithm can be run and false if it cannot.
  - step
```
protected boolean step()
```
    Description copied from class: AbstractAnytimeBatchLearner
    
    Called to take a single step of the learning algorithm.
    
    Specified by:
    
    step in class AbstractAnytimeBatchLearner<java.util.Collection<? extends Vectorizable>,ProbabilisticLatentSemanticAnalysis.Result>
    
    Returns:
    
    True if another step can be taken and false it the algorithm should halt.
  - cleanupAlgorithm
```
protected void cleanupAlgorithm()
```
    Description copied from class: AbstractAnytimeBatchLearner
    
    Called to clean up the learning algorithm's state after learning has finished.
    
    Specified by:
    
    cleanupAlgorithm in class AbstractAnytimeBatchLearner<java.util.Collection<? extends Vectorizable>,ProbabilisticLatentSemanticAnalysis.Result>
  - getResult
```
public ProbabilisticLatentSemanticAnalysis.Result getResult()
```
    Description copied from interface: AnytimeAlgorithm
    
    Gets the current result of the algorithm.
    
    Specified by:
    
    getResult in interface AnytimeAlgorithm<ProbabilisticLatentSemanticAnalysis.Result>
    
    Returns:
    
    Current result of the algorithm.
  - getRandom
```
public java.util.Random getRandom()
```
    Description copied from interface: Randomized
    
    Gets the random number generator used by this object.
    
    Specified by:
    
    getRandom in interface Randomized
    
    Returns:
    
    The random number generator used by this object.
  - setRandom
```
public void setRandom(java.util.Random random)
```
    Description copied from interface: Randomized
    
    Sets the random number generator used by this object.
    
    Specified by:
    
    setRandom in interface Randomized
    
    Parameters:
    
    random - The random number generator for this object to use.
  - getVectorFactory
```
public VectorFactory<? extends Vector> getVectorFactory()
```
    Gets the vector factory to use.
    
    Specified by:
    
    getVectorFactory in interface VectorFactoryContainer
    
    Returns:
    
    The vector factory to use.
  - setVectorFactory
```
public void setVectorFactory(VectorFactory<? extends Vector> vectorFactory)
```
    Sets the vector factory to use.
    
    Parameters:
    
    vectorFactory - The vector factory to use.
  - getMatrixFactory
```
public MatrixFactory<? extends Matrix> getMatrixFactory()
```
    Gets the matrix factory to use.
    
    Returns:
    
    The matrix factory to use.
  - setMatrixFactory
```
public void setMatrixFactory(MatrixFactory<? extends Matrix> matrixFactory)
```
    Sets the matrix factory to use.
    
    Parameters:
    
    matrixFactory - The matrix factory to use.
  - getRequestedRank
```
public int getRequestedRank()
```
    Gets the requested rank to conduct the analysis for. It is the number of latent variables to use.
    
    Returns:
    
    The requested rank. Must be positive.
  - setRequestedRank
```
public void setRequestedRank(int requestedRank)
```
    Sets the requested rank to conduct the analysis for. It is the number of latent variables to use.
    
    Parameters:
    
    requestedRank - The requested rank. Must be positive.
  - getMinimumChange
```
public double getMinimumChange()
```
    Gets the minimum change in log-likelihood to allow before stopping the algorithm.
    
    Returns:
    
    The minimum change in log-likelihood to allow before stopping. Must be non-negative.
  - setMinimumChange
```
public void setMinimumChange(double minimumChange)
```
    Sets the minimum change in log-likelihood to allow before stopping the algorithm.
    
    Parameters:
    
    minimumChange - The minimum change in log-likelihood to allow before stopping. Must be non-negative.

Class ProbabilisticLatentSemanticAnalysis

Nested Class Summary

Field Summary

Fields inherited from class gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner

Fields inherited from class gov.sandia.cognition.algorithm.AbstractAnytimeAlgorithm

Fields inherited from class gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm

Constructor Summary

Method Summary

Methods inherited from class gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner

Methods inherited from class gov.sandia.cognition.algorithm.AbstractAnytimeAlgorithm

Methods inherited from class gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm

Methods inherited from class java.lang.Object

Methods inherited from interface gov.sandia.cognition.algorithm.AnytimeAlgorithm

Methods inherited from interface gov.sandia.cognition.algorithm.IterativeAlgorithm

Methods inherited from interface gov.sandia.cognition.algorithm.StoppableAlgorithm

Field Detail

DEFAULT_REQUESTED_RANK

DEFAULT_MAX_ITERATIONS

DEFAULT_MINIMUM_CHANGE

requestedRank

minimumChange

random

vectorFactory

matrixFactory

documentsByTerms

termCount

documentCount

latentCount

latents

logLikelihood

changeOfLogLikelihood

result

Constructor Detail

ProbabilisticLatentSemanticAnalysis

ProbabilisticLatentSemanticAnalysis

ProbabilisticLatentSemanticAnalysis

ProbabilisticLatentSemanticAnalysis

Method Detail

initializeAlgorithm

step

cleanupAlgorithm

getResult

getRandom

setRandom

getVectorFactory

setVectorFactory

getMatrixFactory

setMatrixFactory

getRequestedRank

setRequestedRank

getMinimumChange

setMinimumChange