Documentation API of the 'org.encog.neural.pnn.BasicPNN' Java class

Class BasicPNN

  • All Implemented Interfaces:
    Serializable, MLInput, MLInputOutput, MLMethod, MLOutput, MLProperties, MLRegression

    public class BasicPNNextends AbstractPNNimplements MLRegression
    This class implements either a: Probabilistic Neural Network (PNN) General Regression Neural Network (GRNN) To use a PNN specify an output mode of classification, to make use of a GRNN specify either an output mode of regression or un-supervised autoassociation. The PNN/GRNN networks are potentially very useful. They share some similarities with RBF-neural networks and also the Support Vector Machine (SVM). These network types directly support the use of classification. The following book was very helpful in implementing PNN/GRNN's in Encog. Advanced Algorithms for Neural Networks: A C++ Sourcebook by Timothy Masters, PhD ( John Wiley & Sons Inc (Computers); April 3, 1995, ISBN: 0471105880
    See Also:
    Serialized Form

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