ART
org.encog.neural.art

Class ART

  • All Implemented Interfaces:
    Serializable, MLMethod, MLProperties
    Direct Known Subclasses:
    ART1


    public class ARTextends BasicML
    Adaptive Resonance Theory (ART) is a form of neural network developed by Stephen Grossberg and Gail Carpenter. There are several versions of the ART neural network, which are numbered ART-1, ART-2 and ART-3. The ART neural network is trained using either a supervised or unsupervised learning algorithm, depending on the version of ART being used. ART neural networks are used for pattern recognition and prediction. Plasticity is an important part for all Adaptive Resonance Theory (ART) neural networks. Unlike most neural networks, ART networks do not have a distinct training and usage stage. The ART network will learn as it is used.
    See Also:
    Serialized Form

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