Package org.encog.neural.networks.training.propagation.scg

Examples of org.encog.neural.networks.training.propagation.scg.ScaledConjugateGradient


  public void testSCG() throws Throwable
  {
    MLDataSet trainingData = new BasicMLDataSet(XOR.XOR_INPUT,XOR.XOR_IDEAL);
   
    BasicNetwork network = NetworkUtil.createXORNetworkUntrained();
    MLTrain bprop = new ScaledConjugateGradient(network, trainingData);
    NetworkUtil.testTraining(bprop,0.04);
  }
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      throw new EncogError(
          "SCG training cannot be used on a method of type: "
              + method.getClass().getName());
    }

    return new ScaledConjugateGradient((BasicNetwork) method, training);
  }
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      if( kFold>0 ) {
        trainingData = this.wrapTrainingData(trainingData);
      }
     
      MLTrain train = new ScaledConjugateGradient(
          (BasicNetwork) file.getObject(), trainingData);
     
      if( kFold>0 ) {
        train = this.wrapTrainer(trainingData,train,kFold);
      }
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      throw new EncogError(
          "SCG training cannot be used on a method of type: "
              + method.getClass().getName());
    }

    return new ScaledConjugateGradient((BasicNetwork) method, training);
  }
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public class ScaledConjugateGradientFactory implements EnsembleTrainFactory {

  @Override
  public MLTrain getTraining(MLMethod mlMethod, MLDataSet trainingData) {
    return (MLTrain) new ScaledConjugateGradient((BasicNetwork) mlMethod, trainingData);
  }
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  public void testSCG() throws Throwable
  {
    MLDataSet trainingData = new BasicMLDataSet(XOR.XOR_INPUT,XOR.XOR_IDEAL);
   
    BasicNetwork network = NetworkUtil.createXORNetworkUntrained();
    MLTrain bprop = new ScaledConjugateGradient(network, trainingData);
    NetworkUtil.testTraining(trainingData,bprop,0.04);
  }
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