weka.classifiers.neural.lvq
Class LvqAlgorithmAncestor

java.lang.Object
  extended by weka.classifiers.Classifier
      extended by weka.classifiers.neural.lvq.AlgorithmAncestor
          extended by weka.classifiers.neural.lvq.LvqAlgorithmAncestor
All Implemented Interfaces:
java.io.Serializable, java.lang.Cloneable, weka.core.OptionHandler, weka.core.WeightedInstancesHandler
Direct Known Subclasses:
Lvq1, Lvq2_1, Lvq3, Olvq1

public abstract class LvqAlgorithmAncestor
extends AlgorithmAncestor

Description: Represents a common ancestor for specific LVQ algorithm implementations. Provides common functionality shared between all LVQ implementations. Provides a framwork to be implemented by specific LVQ implementations for consistent validation, model construction and instance classification.
Copyright (c) Jason Brownlee 2004

Author:
Jason Brownlee
See Also:
Serialized Form

Constructor Summary
LvqAlgorithmAncestor()
           
 
Method Summary
 weka.core.SelectedTag getLearningFunction()
          Return the learning function
 double getLearningRate()
          Return the learning rate
 java.lang.String[] getOptions()
          Returns a list of all common and specific algorithm options
 int getTotalCodebookVectors()
           
 int getTotalTrainingIterations()
          Return total training iterations
 java.lang.String initialisationModeTipText()
          Initialisation mode tip
 java.lang.String learningFunctionTipText()
          Learning function tip
 java.lang.String learningRateTipText()
          Learning rate tip
 java.util.Enumeration listOptions()
          Provides a list of common algorithm options, as well as specific options
 java.lang.String randomSeedTipText()
          Random number seed
 void setLearningFunction(weka.core.SelectedTag l)
          Set learning functiom
 void setLearningRate(double r)
          Set the learning rate
 void setOptions(java.lang.String[] options)
          Set algorithm options, common and specific
 void setTotalCodebookVectors(int i)
           
 void setTotalTrainingIterations(int t)
          Set total training iterations
 java.lang.String totalCodebookVectorsTipText()
          Codebook vectors tip
 java.lang.String totalTrainingIterationsTipText()
          Training iterations tip
 java.lang.String useVotingTipText()
           
 
Methods inherited from class weka.classifiers.neural.lvq.AlgorithmAncestor
addEpochEventListener, buildClassifier, calculateQuantisationError, distributionForInstance, getInitialisationMode, getModel, getSeed, getTotalTrainingBmuHits, getTrainingBmuUsage, getUseVoting, globalInfo, prepareBuildTimeReport, prepareClassDistributionReport, prepareCodebookVectorReport, prepareIndividualClassDistributionReport, prepareTrainingBMUReport, quantisationErrorReport, setInitialisationMode, setPreInitialisedModel, setPrepareBmuStatistis, setSeed, setUseVoting, toString
 
Methods inherited from class weka.classifiers.Classifier
classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug
 
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait
 

Constructor Detail

LvqAlgorithmAncestor

public LvqAlgorithmAncestor()
Method Detail

listOptions

public java.util.Enumeration listOptions()
Provides a list of common algorithm options, as well as specific options

Specified by:
listOptions in interface weka.core.OptionHandler
Overrides:
listOptions in class weka.classifiers.Classifier
Returns:
Enumeration

setOptions

public void setOptions(java.lang.String[] options)
                throws java.lang.Exception
Set algorithm options, common and specific

Specified by:
setOptions in interface weka.core.OptionHandler
Overrides:
setOptions in class weka.classifiers.Classifier
Parameters:
options - - list of options
Throws:
java.lang.Exception

getOptions

public java.lang.String[] getOptions()
Returns a list of all common and specific algorithm options

Specified by:
getOptions in interface weka.core.OptionHandler
Overrides:
getOptions in class weka.classifiers.Classifier

initialisationModeTipText

public java.lang.String initialisationModeTipText()
Initialisation mode tip

Returns:

totalCodebookVectorsTipText

public java.lang.String totalCodebookVectorsTipText()
Codebook vectors tip

Returns:

totalTrainingIterationsTipText

public java.lang.String totalTrainingIterationsTipText()
Training iterations tip

Returns:

learningFunctionTipText

public java.lang.String learningFunctionTipText()
Learning function tip

Returns:

learningRateTipText

public java.lang.String learningRateTipText()
Learning rate tip

Returns:

randomSeedTipText

public java.lang.String randomSeedTipText()
Random number seed

Returns:

useVotingTipText

public java.lang.String useVotingTipText()

setTotalTrainingIterations

public void setTotalTrainingIterations(int t)
Set total training iterations

Parameters:
t -

getTotalTrainingIterations

public int getTotalTrainingIterations()
Return total training iterations

Returns:

setLearningFunction

public void setLearningFunction(weka.core.SelectedTag l)
Set learning functiom

Parameters:
l -

getLearningFunction

public weka.core.SelectedTag getLearningFunction()
Return the learning function

Returns:

setLearningRate

public void setLearningRate(double r)
Set the learning rate

Parameters:
r -

getLearningRate

public double getLearningRate()
Return the learning rate

Returns:

getTotalCodebookVectors

public int getTotalCodebookVectors()
Specified by:
getTotalCodebookVectors in class AlgorithmAncestor
Returns:

setTotalCodebookVectors

public void setTotalCodebookVectors(int i)
Parameters:
i -