Modifier and Type | Class and Description |
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class |
BayesianNetwork
The Bayesian Network is a machine learning method that is based on
probability, and particularly Bayes' Rule.
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Modifier and Type | Class and Description |
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class |
LinearRegression |
Modifier and Type | Class and Description |
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class |
EncogProgram
Holds an Encog Programming Language (EPL) program.
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Modifier and Type | Class and Description |
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class |
SVM
This is a network that is backed by one or more Support Vector Machines
(SVM).
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Modifier and Type | Class and Description |
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class |
CPN
Counterpropagation Neural Networks (CPN) were developed by Professor
Robert Hecht-Nielsen in 1987.
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Modifier and Type | Class and Description |
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class |
FreeformNetwork
Implements a freefrom neural network.
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Modifier and Type | Class and Description |
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class |
NEATNetwork
NEAT networks relieve the programmer of the need to define the hidden layer
structure of the neural network.
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class |
NEATPopulation
A population for a NEAT or HyperNEAT system.
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Modifier and Type | Class and Description |
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class |
BasicNetwork
This class implements a neural network.
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Modifier and Type | Class and Description |
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class |
BasicPNN
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.
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Modifier and Type | Class and Description |
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class |
RBFNetwork
RBF neural network.
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Modifier and Type | Class and Description |
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class |
SOM
A self organizing map neural network.
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