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Uses of BasicML in org.encog.ca.universe.basic |
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Subclasses of BasicML in org.encog.ca.universe.basic | |
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BasicUniverse
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Uses of BasicML in org.encog.ml.bayesian |
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Subclasses of BasicML in org.encog.ml.bayesian | |
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BayesianNetwork
The Bayesian Network is a machine learning method that is based on probability, and particularly Bayes' Rule. |
Uses of BasicML in org.encog.ml.ea.population |
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Subclasses of BasicML in org.encog.ml.ea.population | |
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BasicPopulation
Defines the basic functionality for a population of genomes. |
Uses of BasicML in org.encog.ml.hmm |
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Subclasses of BasicML in org.encog.ml.hmm | |
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class |
HiddenMarkovModel
A Hidden Markov Model (HMM) is a Machine Learning Method that allows for predictions to be made about the hidden states and observations of a given system over time. |
Uses of BasicML in org.encog.ml.prg.train |
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Subclasses of BasicML in org.encog.ml.prg.train | |
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PrgPopulation
A population that contains EncogProgram's. |
Uses of BasicML in org.encog.ml.svm |
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Subclasses of BasicML in org.encog.ml.svm | |
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class |
SVM
This is a network that is backed by one or more Support Vector Machines (SVM). |
Uses of BasicML in org.encog.neural.art |
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Subclasses of BasicML in org.encog.neural.art | |
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class |
ART
Adaptive Resonance Theory (ART) is a form of neural network developed by Stephen Grossberg and Gail Carpenter. |
class |
ART1
Implements an ART1 neural network. |
Uses of BasicML in org.encog.neural.bam |
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Subclasses of BasicML in org.encog.neural.bam | |
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BAM
Bidirectional associative memory (BAM) is a type of neural network developed by Bart Kosko in 1988. |
Uses of BasicML in org.encog.neural.cpn |
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Subclasses of BasicML in org.encog.neural.cpn | |
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CPN
Counterpropagation Neural Networks (CPN) were developed by Professor Robert Hecht-Nielsen in 1987. |
Uses of BasicML in org.encog.neural.freeform |
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Subclasses of BasicML in org.encog.neural.freeform | |
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FreeformNetwork
Implements a freefrom neural network. |
Uses of BasicML in org.encog.neural.neat |
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Subclasses of BasicML in org.encog.neural.neat | |
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class |
NEATPopulation
A population for a NEAT or HyperNEAT system. |
Uses of BasicML in org.encog.neural.networks |
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Subclasses of BasicML in org.encog.neural.networks | |
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class |
BasicNetwork
This class implements a neural network. |
Uses of BasicML in org.encog.neural.pnn |
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Subclasses of BasicML in org.encog.neural.pnn | |
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class |
AbstractPNN
Abstract class to build PNN networks upon. |
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. |
Uses of BasicML in org.encog.neural.rbf |
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Subclasses of BasicML in org.encog.neural.rbf | |
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RBFNetwork
RBF neural network. |
Uses of BasicML in org.encog.neural.som |
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Subclasses of BasicML in org.encog.neural.som | |
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class |
SOM
A self organizing map neural network. |
Uses of BasicML in org.encog.neural.thermal |
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Subclasses of BasicML in org.encog.neural.thermal | |
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class |
BoltzmannMachine
Implements a Boltzmann machine. |
class |
HopfieldNetwork
Implements a Hopfield network. |
class |
ThermalNetwork
The thermal network forms the base class for Hopfield and Boltzmann machines. |
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