- All Known Subinterfaces:
- ArrayGenome, ContainsFlat, EnsembleML, Genome, MLAutoAssocation, MLClassification, MLClustering, MLContext, MLEncodable, MLError, MLInput, MLInputOutput, MLOutput, MLProperties, MLRegression, MLResettable, MLStateSequence, Population
- All Known Implementing Classes:
- AbstractPNN, ART, ART1, BAM, BasicGenome, BasicML, BasicNetwork, BasicPNN, BasicPopulation, BasicUniverse, BayesianNetwork, BoltzmannMachine, CPN, DoubleArrayGenome, EncogProgram, FreeformNetwork, GaussianFitting, GenericEnsembleML, HiddenMarkovModel, HopfieldNetwork, HyperNEATGenome, IntegerArrayGenome, KMeansClustering, LinearRegression, MLMethodGenome, NEATGenome, NEATNetwork, NEATPopulation, PrgPopulation, RBFNetwork, SOM, SVM, ThermalNetwork
public interface MLMethodThis interface is the base for all Encog Machine Learning methods. It defines very little, other than the fact that a subclass is a Machine Learning Method. A MLMethod is an algorithm that accepts data and provides some sort of insight into it. This could be a neural network, support vector machine, clustering algorithm, or something else entirely. Many MLMethods must be trained by a MLTrain object before they are useful.
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