edu.gtts.sautrela.wfsa
Class Trainer

java.lang.Object
  edu.gtts.sautrela.engine.AbstractDataProcessor
      edu.gtts.sautrela.wfsa.Trainer

All Implemented Interfaces:

DataProcessor, java.beans.BeanInfo, java.io.Serializable

public class Trainer
extends AbstractDataProcessor

Author:

mpenagar

See Also:

Serialized Form

Nested Class Summary

static class	Trainer.Method
static class	Trainer.TargetType

Field Summary

Fields inherited from interface java.beans.BeanInfo

ICON_COLOR_16x16, ICON_COLOR_32x32, ICON_MONO_16x16, ICON_MONO_32x32

Constructor Summary

Trainer()

Method Summary

void	editBeanInfo(java.beans.BeanInfo info)
double	getBeam() Getter for property beam.
DefaultDWFSA.InsertionMask	getInsertionMask() Getter for property insertionMask.
java.lang.String	getInsertionSymbolName() Getter for property insertionSymbolName.
double	getMapCount() Getter for property mapCount.
Trainer.Method	getMethod() Getter for property method.
java.lang.String	getOutputFileName() Getter for property outputFileName.
java.lang.String	getSupPropertyName() Getter for property supPropertyName.
java.lang.String	getSupSplitRegex() Getter for property supSplitRegex.
Trainer.TargetType	getTargetType() Getter for property targetType.
java.net.URL	getTargetURL() Getter for property targetURL.
int	getVerbose() Getter for property verbose.
boolean	isFullGCPerformed() Getter for property GCWaited.
static void	main(java.lang.String[] args)
static <S extends State,Y extends Symbol,T extends Transition<S,Y>> double	ML(WFSA<S,Y,T> wfa, java.util.Collection<java.util.List<Y>> data, Trainer.Method method, double beam, int verbose) Trains a WFSA using the Maximun Likelihood criteria
static <S extends State,Y extends Symbol,T extends Transition<S,Y>> double	ML(WFSA<S,Y,T> wfa, java.util.Collection<java.util.List<Y>> data, Trainer.Method method, double beam, int verbose, double mapCount) Trains a WFSA using the Maximun Likelihood criteria
void	process(Buffer in, Buffer out) Processes the input Data.
void	setBeam(double beam) Setter for property beam.
void	setFullGCPerformed(boolean fullGCPerformed) Setter for property fullGCPerformed.
void	setInsertionMask(DefaultDWFSA.InsertionMask mask) Setter for property insertionMask.
void	setInsertionSymbolName(java.lang.String name) Setter for property insertionSymbolName.
void	setMapCount(double mapCount) Setter for property mapCount.
void	setMethod(Trainer.Method method) Setter for property method.
void	setOutputFileName(java.lang.String fileName) Setter for property outputFileName.
void	setSupPropertyName(java.lang.String supPropertyName) Setter for property supPropertyName.
void	setSupSplitRegex(java.lang.String supSplitRegex) Setter for property supSplitRegex.
void	setTargetType(Trainer.TargetType type) Setter for property targetType.
void	setTargetURL(java.net.URL url) Setter for property targetURL.
void	setVerbose(int verbose) Setter for property verbose.

Methods inherited from class edu.gtts.sautrela.engine.AbstractDataProcessor

getAdditionalBeanInfo, getBeanDescriptor, getDefaultEventIndex, getDefaultPropertyIndex, getEventSetDescriptors, getIcon, getMethodDescriptors, getName, getPropertyDescriptors, toString

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

Trainer

public Trainer()

Method Detail

isFullGCPerformed

public boolean isFullGCPerformed()

Getter for property GCWaited.

Returns:

Value of property GCWaited.

setFullGCPerformed

public void setFullGCPerformed(boolean fullGCPerformed)

Setter for property fullGCPerformed.

Parameters:

fullGCPerformed - New value of property fullGCPerformed.

getMethod

public Trainer.Method getMethod()

Getter for property method.

Returns:

Value of property method.

setMethod

public void setMethod(Trainer.Method method)

Setter for property method.

Parameters:

method - New value of property method.

getBeam

public double getBeam()

Getter for property beam.

Returns:

Value of property beam.

setBeam

public void setBeam(double beam)

Setter for property beam.

Parameters:

beam - New value of property beam.

getMapCount

public double getMapCount()

Getter for property mapCount.

Returns:

Value of property mapCount.

setMapCount

public void setMapCount(double mapCount)

Setter for property mapCount.

Parameters:

mapCount - New value of property mapCount.

getOutputFileName

public java.lang.String getOutputFileName()

Getter for property outputFileName.

Returns:

Value of property outputFileName.

setOutputFileName

public void setOutputFileName(java.lang.String fileName)

Setter for property outputFileName.

Parameters:

fileName - New value of property outputFileName.

getTargetURL

public java.net.URL getTargetURL()

Getter for property targetURL.

Returns:

Value of property targetURL.

setTargetURL

public void setTargetURL(java.net.URL url)
                  throws DataProcessorException

Setter for property targetURL.

Parameters:

url - New value of property targetURL.

Throws:

DataProcessorException

getTargetType

public Trainer.TargetType getTargetType()

Getter for property targetType.

Returns:

Value of property targetType.

setTargetType

public void setTargetType(Trainer.TargetType type)
                   throws DataProcessorException

Setter for property targetType.

Parameters:

type - New value of property targetType.

Throws:

DataProcessorException

getInsertionMask

public DefaultDWFSA.InsertionMask getInsertionMask()

Getter for property insertionMask.

Returns:

Value of property insertionPolicy.

setInsertionMask

public void setInsertionMask(DefaultDWFSA.InsertionMask mask)

Setter for property insertionMask.

Parameters:

mask - New value of property insertionMask.

getInsertionSymbolName

public java.lang.String getInsertionSymbolName()

Getter for property insertionSymbolName.

Returns:

Value of property insertionSymbolName.

setInsertionSymbolName

public void setInsertionSymbolName(java.lang.String name)

Setter for property insertionSymbolName.

Parameters:

name - New value of property insertionSymbolName.

getVerbose

public int getVerbose()

Getter for property verbose.

Returns:

Value of property verbose.

setVerbose

public void setVerbose(int verbose)

Setter for property verbose.

Parameters:

verbose - New value of property verbose.

getSupPropertyName

public java.lang.String getSupPropertyName()

Getter for property supPropertyName.

Returns:

Value of property supPropertyName.

setSupPropertyName

public void setSupPropertyName(java.lang.String supPropertyName)

Setter for property supPropertyName.

Parameters:

supPropertyName - New value of property supPropertyName.

getSupSplitRegex

public java.lang.String getSupSplitRegex()

Getter for property supSplitRegex.

Returns:

Value of property supSplitRegex.

setSupSplitRegex

public void setSupSplitRegex(java.lang.String supSplitRegex)

Setter for property supSplitRegex.

Parameters:

supPropertyName - New value of property supSplitRegex.

process

public void process(Buffer in,
                    Buffer out)
             throws DataProcessorException

Processes the input Data. Multidimensional input data is treated as multidimensional symbol. Thus WFSAs with single dimmension symbols must receive scalar Data sequencially, whereas multidimensional ones (like CHMM) must receive multidimensional data.

Parameters:

in - Input Buffer

out - Output Buffer

Throws:

DataProcessorException

ML

public static <S extends State,Y extends Symbol,T extends Transition<S,Y>> double ML(WFSA<S,Y,T> wfa,
                                                                                     java.util.Collection<java.util.List<Y>> data,
                                                                                     Trainer.Method method,
                                                                                     double beam,
                                                                                     int verbose)

Trains a WFSA using the Maximun Likelihood criteria

Parameters:

wfa - the WFSA to be trained

data - the Collection of Symbol List to be used as training data

method - the Method to be used for the training

beam - logBeam for pruning (<0.0 for no prunning)

ML

public static <S extends State,Y extends Symbol,T extends Transition<S,Y>> double ML(WFSA<S,Y,T> wfa,
                                                                                     java.util.Collection<java.util.List<Y>> data,
                                                                                     Trainer.Method method,
                                                                                     double beam,
                                                                                     int verbose,
                                                                                     double mapCount)

Trains a WFSA using the Maximun Likelihood criteria

Parameters:

wfa - the WFSA to be trained

data - the Collection of Symbol List to be used as training data

method - the Method to be used for the training

beam - logBeam for pruning (negative for no prunning)

mapCount - initial posterior probability count for MAP training

editBeanInfo

public void editBeanInfo(java.beans.BeanInfo info)

Overrides:

editBeanInfo in class AbstractDataProcessor

main

public static void main(java.lang.String[] args)
                 throws java.lang.Exception

Throws:

java.lang.Exception