org.encog.neural.networks.training

Class TrainingSetScore

java.lang.Object

org.encog.neural.networks.training.TrainingSetScore

All Implemented Interfaces:

CalculateScore

public class TrainingSetScore
extends Object
implements CalculateScore

Calculate a score based on a training set. This class allows simulated annealing or genetic algorithms just as you would any other training set based training method. The method must support regression (MLRegression).

Constructor Summary

Constructors

Constructor and Description
TrainingSetScore(MLDataSet training) Construct a training set score calculation.

Method Summary

Methods

Modifier and Type	Method and Description
double	calculateScore(MLMethod method) Calculate the score for the network.
boolean	requireSingleThreaded()
boolean	shouldMinimize() A training set based score should always seek to lower the error, as a result, this method always returns true.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

TrainingSetScore

public TrainingSetScore(MLDataSet training)

Construct a training set score calculation.

Parameters:

training - The training data to use.

Method Detail

calculateScore

public double calculateScore(MLMethod method)

Calculate the score for the network.

Specified by:

calculateScore in interface CalculateScore

Parameters:

method - The network to calculate for.

Returns:

The score.

shouldMinimize

public boolean shouldMinimize()

A training set based score should always seek to lower the error, as a result, this method always returns true.

Specified by:

shouldMinimize in interface CalculateScore

Returns:

Returns true.

requireSingleThreaded

public boolean requireSingleThreaded()

Specified by:

requireSingleThreaded in interface CalculateScore

Returns:

True, if this score function cannot be done in parallel.