MLTrain
org.encog.ml.train

Interface MLTrain

    • Method Detail

      • isTrainingDone

        boolean isTrainingDone()
        Returns:
        True if training can progress no further.
      • getTraining

        MLDataSet getTraining()
        Returns:
        The training data to use.
      • iteration

        void iteration()
        Perform one iteration of training.
      • getError

        double getError()
        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.
      • finishTraining

        void finishTraining()
        Should be called once training is complete and no more iterations are needed. Calling iteration again will simply begin the training again, and require finishTraining to be called once the new training session is complete. It is particularly important to call finishTraining for multithreaded training techniques.
      • iteration

        void iteration(int count)
        Perform a number of training iterations.
        Parameters:
        count - The number of iterations to perform.
      • getIteration

        int getIteration()
        Returns:
        The current training iteration.
      • canContinue

        boolean canContinue()
        Returns:
        True if the training can be paused, and later continued.
      • pause

        TrainingContinuation pause()
        Pause the training to continue later.
        Returns:
        A training continuation object.
      • resume

        void resume(TrainingContinuation state)
        Resume training.
        Parameters:
        state - The training continuation object to use to continue.
      • addStrategy

        void addStrategy(Strategy strategy)
        Training strategies can be added to improve the training results. There are a number to choose from, and several can be used at once.
        Parameters:
        strategy - The strategy to add.
      • getMethod

        MLMethod getMethod()
        Get the current best machine learning method from the training.
        Returns:
        The best machine learningm method.
      • getStrategies

        List<Strategy> getStrategies()
        Returns:
        The strategies to use.
      • setError

        void setError(double error)
        Parameters:
        error - Set the current error rate. This is usually used by training strategies.
      • setIteration

        void setIteration(int iteration)
        Set the current training iteration.
        Parameters:
        iteration - Iteration.

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