Modifier and Type | Class and Description |
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class |
BasicUniverse |
Modifier and Type | Class and Description |
---|---|
class |
BasicML
A class that provides basic property functionality for the MLProperties
interface.
|
Modifier and Type | Class and Description |
---|---|
class |
BayesianNetwork
The Bayesian Network is a machine learning method that is based on
probability, and particularly Bayes' Rule.
|
Modifier and Type | Class and Description |
---|---|
class |
BasicPopulation
Defines the basic functionality for a population of genomes.
|
Modifier and Type | Class and Description |
---|---|
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.
|
Modifier and Type | Class and Description |
---|---|
class |
PrgPopulation
A population that contains EncogProgram's.
|
Modifier and Type | Class and Description |
---|---|
class |
SVM
This is a network that is backed by one or more Support Vector Machines
(SVM).
|
Modifier and Type | Class and Description |
---|---|
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.
|
Modifier and Type | Class and Description |
---|---|
class |
BAM
Bidirectional associative memory (BAM) is a type of neural network
developed by Bart Kosko in 1988.
|
Modifier and Type | Class and Description |
---|---|
class |
CPN
Counterpropagation Neural Networks (CPN) were developed by Professor
Robert Hecht-Nielsen in 1987.
|
Modifier and Type | Class and Description |
---|---|
class |
FreeformNetwork
Implements a freefrom neural network.
|
Modifier and Type | Class and Description |
---|---|
class |
NEATPopulation
A population for a NEAT or HyperNEAT system.
|
Modifier and Type | Class and Description |
---|---|
class |
BasicNetwork
This class implements a neural network.
|
Modifier and Type | Class and Description |
---|---|
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.
|
Modifier and Type | Class and Description |
---|---|
class |
RBFNetwork
RBF neural network.
|
Modifier and Type | Class and Description |
---|---|
class |
SOM
A self organizing map neural network.
|
Modifier and Type | Class and Description |
---|---|
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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