SVMSearchTrain
org.encog.ml.svm.training

Class SVMSearchTrain

  • All Implemented Interfaces:
    MLTrain


    public class SVMSearchTrainextends BasicTraining
    Provides training for Support Vector Machine networks.
    • 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.
      • 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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