反规范化MLData在Encog

我已归一化的一组使用以下代码的数据：反规范化MLData在Encog

public static void main(String[] args) { 

//To Normalize the data 
    File sourcefiletotrain=new File("E:\\Shreyas-Internship\\RforLF\\dataforAnn.csv"); 
    File targetfiletotrain=new File("E:\\Shreyas-Internship\\RforLF\\ideal.csv"); 
    EncogAnalyst analyst=new EncogAnalyst(); 
    AnalystWizard wizard=new AnalystWizard(analyst); 
    wizard.setGoal(AnalystGoal.Regression); 
    wizard.wizard(sourcefiletotrain, false,AnalystFileFormat.DECPNT_COMMA); 
    final AnalystNormalizeCSV norm=new AnalystNormalizeCSV(); 
    norm.analyze(sourcefiletotrain, false, ENGLISH, analyst); 
    norm.normalize(targetfiletotrain);

然后我已经使用以下数据来训练，并使用Encog运行神经网络。我面临的问题是我无法将价值回归到实际形式。培训和运行神经网络的代码是：

//To Train the Neural Network 
    CSVNeuralDataSet fileread=new CSVNeuralDataSet("E:\\Shreyas-Internship\\RforLF\\ideal.csv",4,1,true); 
    BasicNetwork network=new BasicNetwork(); 
    network.addLayer(new BasicLayer(4)); 
    network.addLayer(new BasicLayer(20)); 
    network.addLayer(new BasicLayer(1)); 
    network.getStructure().finalizeStructure(); 
    network.reset(); 
    MLDataSet trainingset=new BasicMLDataSet(fileread); 
    MLTrain train= new ResilientPropagation(network,trainingset); 
    int epoch=1; 
    do{ 

     train.iteration(); 
     System.out.println("Epoch " +epoch+ " Error:" +train.getError()); 
     epoch++; 
     }while((train.getError()>0.01)&&(epoch<=500)); 



    //To run the Neural Network 
    System.out.println("Neural Network Results"); 
    for (MLDataPair pair: trainingset){ 
     final MLData output=network.compute(pair.getInput()); 
     System.out.println("actual="+output.getData(0)+ "\tideal="+pair.getIdeal().getData(0));//pair.getInput().getData(0)+" ,"+pair.getInput().getData(1)+" ,"+pair.getInput().getData(2)+" ,"+pair.getInput().getData(3)+" ,"+pair.getInput().getData(4)+" ,"+pair.getInput().getData(5)+ 


    } 


}

的疑问是我如何进一步继续获得非规范化的输出为MLData

来源

2015-11-05 Shreyas Karnick

此外，如果在Encog中有一个替代方案可用于规范化，训练，运行和取消规范化一组数据，请让我知道。 –

您可以使用encog NormalizedField类：

def denormalize(double high, double low, double normalizedValue){ 
    NormalizedField normalizedField = new NormalizedField(high, low) 
    normalizedField.deNormalize(normalizedValue) 
}

其中高和低是用于标准化的范围。

来源

2015-12-10 22:40:11

反规范化MLData在Encog

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