com.ibm.able.beans.bayes
Class AbleNaiveBayes

java.lang.Object
  com.ibm.able.AbleObject
      com.ibm.able.beans.bayes.AbleNaiveBayes

All Implemented Interfaces:

AbleBean, AbleDataBufferManager, AbleEventListener, AbleEventListenerManager, AbleEventQueueManager, AbleEventQueueProcessor, AblePropertyChangeManager, AbleSerializable, java.io.Serializable

public class AbleNaiveBayes

extends AbleObject

See Also:

Serialized Form

Field Summary

protected int[][]	data
protected int[]	inNum
protected int[]	labels
protected NaiveBayes	NB
protected int	netMode
protected int	netNumRecs
protected int	netRecInx
protected int	nfeatures
protected int	ninst
protected int	nlabels
protected int	numInputs
protected int	numOutputs
protected int[]	nvals
protected int	nvalues
protected double[]	outNum

Fields inherited from class com.ibm.able.AbleObject

changed, chgSupport, comment, dataFlowEnabled, defaultName, destBufferConnections, eventQueue, fileName, inputBuffer, listeners, logger, name, outputBuffer, parent, properties, propertyConnectionMgr, sourceBufferConnections, state, stateChgSupport, trace

Constructor Summary

AbleNaiveBayes()
construct an AbleNaiveBayes bean

AbleNaiveBayes(int ncls, int nftr, int[] nval, int m, double[] cpriors, double[][][] ppriors)
construct AbleNaiveBayes bean with the explicitly specified parameters ncls - number of class labels nftr - number of features nval - number of values per each feature (assuming nominal - discrete finite-valued - features) cpriors - prior probability distribution over class labels m - equivalent sample size ppriors - prior estimates of the probabilities P(f|C) (used for Bayesian parameter estimation with equivalent sample size method)

AbleNaiveBayes(java.lang.String name)
construct an AbleNaiveBayes bean

Method Summary

double	getAccuracy()
double	getAvgLikelihood()
double	getAvgLogLikelihood()
double[]	getClassPriors()
double[]	getClassProb()
int[][]	getConfusionMatrix()
double[][][]	getCPT()
double[]	getEqSampleSize()
int	getNClasses()
int	getNetMode()
int	getNetNumRecs()
int	getNetRecInx()
int	getNFeatures()
int[]	getNFValues()
void	init() Initialize the bean Read in the file and create the Naive Bayes Network
protected void	initFromImport() try to figure out the Bayes network architecture from an AbleImport and DataSet object
void	process() Process a single record from the input buffer if in train mode, add info to the network if in test mode, classify it and place the class index in the output buffer
void	processTimerEvent() Not used in this class
void	reset() Reset this bean to its "initialized" state.
void	setClassPriors(double[] cpriors)
void	setNClasses(int ncls)
void	setNetMode(int mode) train (build hypothesis) or test(classify) modes
void	setNFeatures(int nftr, int[] nfv)

Methods inherited from class com.ibm.able.AbleObject

addAbleEventListener, addDestBufferConnection, addPropertyChangeListener, addPropertyConnection, addSourceBufferConnection, addStateChangeListener, dataChanged, firePropertyChange, flushAbleEventQueue, getAbleEventListeners, getAbleEventProcessingEnabled, getAbleEventQueueSize, getComment, getDestBufferConnections, getFileName, getInputBuffer, getInputBuffer, getInputBufferAsString, getInputBufferAsStringArray, getInputBufferContents, getLogger, getName, getOutputBuffer, getOutputBuffer, getOutputBufferAsString, getOutputBufferAsStringArray, getOutputBufferContents, getParent, getProperties, getProperty, getPropertyChangeListeners, getPropertyConnectionManager, getSleepTime, getSourceBufferConnections, getState, getTraceLogger, handleAbleEvent, hasInputBuffer, hasOutputBuffer, init, isAbleEventPostingEnabled, isAbleEventProcessingEnabled, isChanged, isConnectable, isDataFlowEnabled, isTimerEventProcessingEnabled, notifyAbleEventListeners, process, processAbleEvent, processBufferConnections, processNoEventProcessingEnabledSituation, quitAll, quitEnabledEventProcessing, removeAbleEventListener, removeAllAbleEventListeners, removeAllBufferConnections, removeAllConnections, removeAllPropertyConnections, removeDestBufferConnection, removeProperty, removePropertyChangeListener, removePropertyConnection, removeSourceBufferConnection, removeStateChangeListener, restartEnabledEventProcessing, restoreFromFile, restoreFromFile, restoreFromSerializedFile, restoreFromStream, resumeAll, resumeEnabledEventProcessing, saveToFile, saveToFile, setAbleEventProcessingEnabled, setChanged, setComment, setDataFlowEnabled, setFileName, setInputBuffer, setInputBuffer, setLogger, setName, setOutputBuffer, setOutputBuffer, setParent, setProperties, setProperty, setSleepTime, setState, setTimerEventProcessingEnabled, setTraceLogger, sourceConnectionsOK, startEnabledEventProcessing, suspendAll, suspendEnabledEventProcessing

Methods inherited from class java.lang.Object

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

Field Detail

NB

protected NaiveBayes NB

data

protected int[][] data

labels

protected int[] labels

nvals

protected int[] nvals

nlabels

protected int nlabels

nfeatures

protected int nfeatures

nvalues

protected int nvalues

ninst

protected int ninst

numInputs

protected int numInputs

numOutputs

protected int numOutputs

inNum

protected int[] inNum

outNum

protected double[] outNum

netMode

protected int netMode

netNumRecs

protected int netNumRecs

netRecInx

protected int netRecInx

Constructor Detail

AbleNaiveBayes

public AbleNaiveBayes()
               throws AbleException

construct an AbleNaiveBayes bean

AbleNaiveBayes

public AbleNaiveBayes(java.lang.String name)
               throws AbleException

construct an AbleNaiveBayes bean

AbleNaiveBayes

public AbleNaiveBayes(int ncls,
                      int nftr,
                      int[] nval,
                      int m,
                      double[] cpriors,
                      double[][][] ppriors)
               throws AbleException

construct AbleNaiveBayes bean with the explicitly specified parameters ncls - number of class labels nftr - number of features nval - number of values per each feature (assuming nominal - discrete finite-valued - features) cpriors - prior probability distribution over class labels m - equivalent sample size ppriors - prior estimates of the probabilities P(f|C) (used for Bayesian parameter estimation with equivalent sample size method)

Method Detail

getNetMode

public int getNetMode()

getNetNumRecs

public int getNetNumRecs()

getNetRecInx

public int getNetRecInx()

setNetMode

public void setNetMode(int mode)

train (build hypothesis) or test(classify) modes

init

public void init()
          throws AbleException

Initialize the bean Read in the file and create the Naive Bayes Network

Specified by:

init in interface AbleBean

Overrides:

init in class AbleObject

Throws:

AbleException - If an error occurs.

See Also:

AbleObject.startEnabledEventProcessing()

reset

public void reset()

Description copied from class: AbleObject

Reset this bean to its "initialized" state.

This base method has no default implementation. It only provides tracing.

Specified by:

reset in interface AbleBean

Overrides:

reset in class AbleObject

See Also:

AbleBean.reset()

process

public void process()
             throws AbleException

Process a single record from the input buffer if in train mode, add info to the network if in test mode, classify it and place the class index in the output buffer

Specified by:

process in interface AbleBean

Overrides:

process in class AbleObject

Throws:

AbleException

See Also:

AbleObject.inputBuffer, AbleObject.outputBuffer, AbleBean.process()

processTimerEvent

public void processTimerEvent()

Not used in this class

Specified by:

processTimerEvent in interface AbleEventQueueProcessor

Overrides:

processTimerEvent in class AbleObject

initFromImport

protected void initFromImport()
                       throws AbleException

try to figure out the Bayes network architecture from an AbleImport and DataSet object

Throws:

AbleException

getNClasses

public int getNClasses()

getNFeatures

public int getNFeatures()

getNFValues

public int[] getNFValues()

getEqSampleSize

public double[] getEqSampleSize()

getCPT

public double[][][] getCPT()

getClassPriors

public double[] getClassPriors()

getAvgLikelihood

public double getAvgLikelihood()

getAvgLogLikelihood

public double getAvgLogLikelihood()

getAccuracy

public double getAccuracy()

getClassProb

public double[] getClassProb()

getConfusionMatrix

public int[][] getConfusionMatrix()

setNClasses

public void setNClasses(int ncls)

setNFeatures

public void setNFeatures(int nftr,
                         int[] nfv)

setClassPriors

public void setClassPriors(double[] cpriors)