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## Uses of Interface
org.encog.ml.MLProperties

Packages that use MLProperties
org.encog.ca.universe.basic |
org.encog.ml |
org.encog.ml.bayesian |
org.encog.ml.ea.population |
org.encog.ml.hmm |
org.encog.ml.prg.train |
org.encog.ml.svm |
org.encog.neural.art |
org.encog.neural.bam |
org.encog.neural.cpn |
org.encog.neural.freeform |
org.encog.neural.neat |
org.encog.neural.networks |
org.encog.neural.pnn |
org.encog.neural.rbf |
org.encog.neural.som |
org.encog.neural.thermal |

Uses of MLProperties in org.encog.ca.universe.basic

Classes in org.encog.ca.universe.basic that implement MLProperties
`class` | `BasicUniverse`

Uses of MLProperties in org.encog.ml

Classes in org.encog.ml that implement MLProperties
`class` | `BasicML` A class that provides basic property functionality for the MLProperties interface.

Uses of MLProperties in org.encog.ml.bayesian

Classes in org.encog.ml.bayesian that implement MLProperties
`class` | `BayesianNetwork` The Bayesian Network is a machine learning method that is based on probability, and particularly Bayes' Rule.

Uses of MLProperties in org.encog.ml.ea.population

Classes in org.encog.ml.ea.population that implement MLProperties
`class` | `BasicPopulation` Defines the basic functionality for a population of genomes.

Uses of MLProperties in org.encog.ml.hmm

Classes in org.encog.ml.hmm that implement MLProperties
`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 MLProperties in org.encog.ml.prg.train

Classes in org.encog.ml.prg.train that implement MLProperties
`class` | `PrgPopulation` A population that contains EncogProgram's.

Uses of MLProperties in org.encog.ml.svm

Classes in org.encog.ml.svm that implement MLProperties
`class` | `SVM` This is a network that is backed by one or more Support Vector Machines (SVM).

Uses of MLProperties in org.encog.neural.art

Classes in org.encog.neural.art that implement MLProperties
`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 MLProperties in org.encog.neural.bam

Classes in org.encog.neural.bam that implement MLProperties
`class` | `BAM` Bidirectional associative memory (BAM) is a type of neural network developed by Bart Kosko in 1988.

Uses of MLProperties in org.encog.neural.cpn

Classes in org.encog.neural.cpn that implement MLProperties
`class` | `CPN` Counterpropagation Neural Networks (CPN) were developed by Professor Robert Hecht-Nielsen in 1987.

Uses of MLProperties in org.encog.neural.freeform

Classes in org.encog.neural.freeform that implement MLProperties
`class` | `FreeformNetwork` Implements a freefrom neural network.

Uses of MLProperties in org.encog.neural.neat

Classes in org.encog.neural.neat that implement MLProperties
`class` | `NEATPopulation` A population for a NEAT or HyperNEAT system.

Uses of MLProperties in org.encog.neural.networks

Classes in org.encog.neural.networks that implement MLProperties
`class` | `BasicNetwork` This class implements a neural network.

Uses of MLProperties in org.encog.neural.pnn

Classes in org.encog.neural.pnn that implement MLProperties
`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 MLProperties in org.encog.neural.rbf

Classes in org.encog.neural.rbf that implement MLProperties
`class` | `RBFNetwork` RBF neural network.

Uses of MLProperties in org.encog.neural.som

Classes in org.encog.neural.som that implement MLProperties
`class` | `SOM` A self organizing map neural network.

Uses of MLProperties in org.encog.neural.thermal

Classes in org.encog.neural.thermal that implement MLProperties
`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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