MLDataPair
org.encog.ml.data

Interface MLDataPair

  • All Known Subinterfaces:
    NeuralDataPair
    All Known Implementing Classes:
    BasicMLDataPair, BasicNeuralDataPair, ClusterRow


    public interface MLDataPair
    Training data is stored in two ways, depending on if the data is for supervised, or unsupervised training. For unsupervised training just an input value is provided, and the ideal output values are null. For supervised training both input and the expected ideal outputs are provided. This interface abstracts classes that provide a holder for both of these two data items.
    • Method Detail

      • getIdealArray

        double[] getIdealArray()
        Returns:
        The ideal data that the machine learning method should produce for the specified input.
      • getInputArray

        double[] getInputArray()
        Returns:
        The input that the neural network
      • setIdealArray

        void setIdealArray(double[] data)
        Set the ideal data, the desired output.
        Parameters:
        data - The ideal data.
      • setInputArray

        void setInputArray(double[] data)
        Set the input.
        Parameters:
        data - The input.
      • isSupervised

        boolean isSupervised()
        Returns:
        True if this training pair is supervised. That is, it has both input and ideal data.
      • getIdeal

        MLData getIdeal()
        Returns:
        The ideal data that the neural network should produce for the specified input.
      • getInput

        MLData getInput()
        Returns:
        The input that the neural network
      • getSignificance

        double getSignificance()
        Get the significance, 1.0 is neutral.
        Returns:
        The significance.
      • setSignificance

        void setSignificance(double s)
        Set the significance, 1.0 is neutral.
        Parameters:
        s - The significance.

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