org.encog.ml.svm.training
Class SVMSearchTrain

java.lang.Object
  extended by org.encog.ml.train.BasicTraining
      extended by org.encog.ml.svm.training.SVMSearchTrain
All Implemented Interfaces:
MLTrain

public class SVMSearchTrain
extends BasicTraining

Provides training for Support Vector Machine networks.


Field Summary
static double DEFAULT_CONST_BEGIN
          The default starting number for C.
static double DEFAULT_CONST_END
          The default ending number for C.
static double DEFAULT_CONST_STEP
          The default step for C.
static double DEFAULT_GAMMA_BEGIN
          The default gamma begin.
static double DEFAULT_GAMMA_END
          The default gamma end.
static double DEFAULT_GAMMA_STEP
          The default gamma step.
 
Constructor Summary
SVMSearchTrain(SVM method, MLDataSet training)
          Construct a trainer for an SVM network.
 
Method Summary
 boolean canContinue()
          
 void finishTraining()
          Should be called after training has completed and the iteration method will not be called any further.
 double getBestConst()
           
 double getBestGamma()
           
 double getConstBegin()
           
 double getConstEnd()
           
 double getConstStep()
           
 int getFold()
           
 double getGammaBegin()
           
 double getGammaEnd()
           
 double getGammaStep()
           
 MLMethod getMethod()
          Get the current best machine learning method from the training.
 boolean isTrainingDone()
           
 void iteration()
          Perform one training iteration.
 TrainingContinuation pause()
          Pause the training to continue later.
 void resume(TrainingContinuation state)
          Resume training.
 void setBestConst(double bestConst)
           
 void setBestGamma(double bestGamma)
           
 void setConstBegin(double theConstBegin)
           
 void setConstEnd(double theConstEnd)
           
 void setConstStep(double theConstStep)
           
 void setFold(int theFold)
           
 void setGammaBegin(double theGammaBegin)
           
 void setGammaEnd(double theGammaEnd)
           
 void setGammaStep(double theGammaStep)
           
 
Methods inherited from class org.encog.ml.train.BasicTraining
addStrategy, getError, getImplementationType, getIteration, getStrategies, getTraining, iteration, postIteration, preIteration, setError, setIteration, setTraining
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Field Detail

DEFAULT_CONST_BEGIN

public static final double DEFAULT_CONST_BEGIN
The default starting number for C.

See Also:
Constant Field Values

DEFAULT_CONST_END

public static final double DEFAULT_CONST_END
The default ending number for C.

See Also:
Constant Field Values

DEFAULT_CONST_STEP

public static final double DEFAULT_CONST_STEP
The default step for C.

See Also:
Constant Field Values

DEFAULT_GAMMA_BEGIN

public static final double DEFAULT_GAMMA_BEGIN
The default gamma begin.

See Also:
Constant Field Values

DEFAULT_GAMMA_END

public static final double DEFAULT_GAMMA_END
The default gamma end.

See Also:
Constant Field Values

DEFAULT_GAMMA_STEP

public static final double DEFAULT_GAMMA_STEP
The default gamma step.

See Also:
Constant Field Values
Constructor Detail

SVMSearchTrain

public SVMSearchTrain(SVM method,
                      MLDataSet training)
Construct a trainer for an SVM network.

Parameters:
method - The method to train.
training - The training data for this network.
Method Detail

canContinue

public boolean canContinue()

Returns:
True if the training can be paused, and later continued.

finishTraining

public void finishTraining()
Should be called after training has completed and the iteration method will not be called any further.

Specified by:
finishTraining in interface MLTrain
Overrides:
finishTraining in class BasicTraining

getConstBegin

public double getConstBegin()
Returns:
the constBegin

getConstEnd

public double getConstEnd()
Returns:
the constEnd

getConstStep

public double getConstStep()
Returns:
the constStep

getFold

public int getFold()
Returns:
the fold

getGammaBegin

public double getGammaBegin()
Returns:
the gammaBegin

getGammaEnd

public double getGammaEnd()
Returns:
the gammaEnd

getGammaStep

public double getGammaStep()
Returns:
the gammaStep

getMethod

public MLMethod getMethod()
Get the current best machine learning method from the training.

Returns:
The best machine learningm method.

isTrainingDone

public boolean isTrainingDone()
Specified by:
isTrainingDone in interface MLTrain
Overrides:
isTrainingDone in class BasicTraining
Returns:
True if the training is done.

iteration

public void iteration()
Perform one training iteration.


pause

public TrainingContinuation pause()
Pause the training to continue later.

Returns:
A training continuation object.

resume

public void resume(TrainingContinuation state)
Resume training.

Parameters:
state - The training continuation object to use to continue.

setConstBegin

public void setConstBegin(double theConstBegin)
Parameters:
theConstBegin - the constBegin to set

setConstEnd

public void setConstEnd(double theConstEnd)
Parameters:
theConstEnd - the constEnd to set

setConstStep

public void setConstStep(double theConstStep)
Parameters:
theConstStep - the constStep to set

setFold

public void setFold(int theFold)
Parameters:
theFold - the fold to set

setGammaBegin

public void setGammaBegin(double theGammaBegin)
Parameters:
theGammaBegin - the gammaBegin to set

setGammaEnd

public final void setGammaEnd(double theGammaEnd)
Parameters:
theGammaEnd - the gammaEnd to set.

setGammaStep

public final void setGammaStep(double theGammaStep)
Parameters:
theGammaStep - the gammaStep to set

getBestConst

public double getBestConst()
Returns:
the bestConst

setBestConst

public void setBestConst(double bestConst)
Parameters:
bestConst - the bestConst to set

getBestGamma

public double getBestGamma()
Returns:
the bestGamma

setBestGamma

public void setBestGamma(double bestGamma)
Parameters:
bestGamma - the bestGamma to set


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