FreeformPropagationTraining
org.encog.neural.freeform.training

Class FreeformPropagationTraining

    • Constructor Detail

      • FreeformPropagationTraining

        public FreeformPropagationTraining()
        Don't use this constructor, it is for serialization only.
    • Method Detail

      • canContinue

        public boolean canContinue()
        Specified by:
        canContinue in interface MLTrain
        Returns:
        True if the training can be paused, and later continued.
      • getError

        public double getError()
        Description copied from class: BasicTraining
        Specified by:
        getError in interface MLTrain
        Overrides:
        getError in class BasicTraining
        Returns:
        Returns the training error. This value is calculated as the training data is evaluated by the iteration function. This has two important ramifications. First, the value returned by getError() is meaningless prior to a call to iteration. Secondly, the error is calculated BEFORE training is applied by the call to iteration. The timing of the error calculation is done for performance reasons.
      • getMethod

        public MLMethod getMethod()
        Description copied from interface: MLTrain
        Get the current best machine learning method from the training.
        Specified by:
        getMethod in interface MLTrain
        Returns:
        The best machine learningm method.
      • isFixFlatSopt

        public boolean isFixFlatSopt()
      • iteration

        public void iteration()
        Description copied from interface: MLTrain
        Perform one iteration of training.
        Specified by:
        iteration in interface MLTrain
      • iteration

        public void iteration(int count)
        Description copied from class: BasicTraining
        Perform the specified number of training iterations. This is a basic implementation that just calls iteration the specified number of times. However, some training methods, particularly with the GPU, benefit greatly by calling with higher numbers than 1.
        Specified by:
        iteration in interface MLTrain
        Overrides:
        iteration in class BasicTraining
        Parameters:
        count - The number of training iterations.
      • setError

        public void setError(double theError)
        Specified by:
        setError in interface MLTrain
        Overrides:
        setError in class BasicTraining
        Parameters:
        theError - Set the current error rate. This is usually used by training strategies.
      • setFixFlatSopt

        public void setFixFlatSopt(boolean fixFlatSopt)
      • setIteration

        public void setIteration(int iteration)
        Description copied from interface: MLTrain
        Set the current training iteration.
        Specified by:
        setIteration in interface MLTrain
        Overrides:
        setIteration in class BasicTraining
        Parameters:
        iteration - the iteration to set

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