org.encog.neural.rbf.training
Class SVDTraining

java.lang.Object
  extended by org.encog.ml.train.BasicTraining
      extended by org.encog.neural.rbf.training.SVDTraining
All Implemented Interfaces:
MLTrain

public class SVDTraining
extends BasicTraining

Train a RBF neural network using a SVD. Contributed to Encog By M.Fletcher and M.Dean University of Cambridge, Dept. of Physics, UK


Constructor Summary
SVDTraining(RBFNetwork network, MLDataSet training)
          Construct the training object.
 
Method Summary
 boolean canContinue()
           
 void flatToMatrix(double[] flat, int start, double[][] matrix)
           
 RBFNetwork getMethod()
          Get the current best machine learning method from the training.
 void iteration()
          Perform one iteration.
 void matrixToFlat(double[][] matrix, double[] flat, int start)
          Convert the matrix to flat.
 TrainingContinuation pause()
          Pause the training to continue later.
 void resume(TrainingContinuation state)
          Resume training.
 
Methods inherited from class org.encog.ml.train.BasicTraining
addStrategy, finishTraining, getError, getImplementationType, getIteration, getStrategies, getTraining, isTrainingDone, iteration, postIteration, preIteration, setError, setIteration, setTraining
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

SVDTraining

public SVDTraining(RBFNetwork network,
                   MLDataSet training)
Construct the training object.

Parameters:
network - The network to train. Must have a single output neuron.
training - The training data to use. Must be indexable.
Method Detail

canContinue

public boolean canContinue()
Returns:
True if the training can be paused, and later continued.

flatToMatrix

public void flatToMatrix(double[] flat,
                         int start,
                         double[][] matrix)

getMethod

public RBFNetwork getMethod()
Get the current best machine learning method from the training.

Returns:
The best machine learningm method.

iteration

public void iteration()
Perform one iteration.


matrixToFlat

public void matrixToFlat(double[][] matrix,
                         double[] flat,
                         int start)
Convert the matrix to flat.

Parameters:
matrix - The matrix.
flat - Flat array.
start - WHere to start.

pause

public TrainingContinuation pause()
Pause the training to continue later.

Returns:
A training continuation object.

resume

public void resume(TrainingContinuation state)
Resume training.

Parameters:
state - The training continuation object to use to continue.


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