Encog C＃RBF网络，如何启动？

Question

我经历了整个文档，没有找到如何设置RBF网络。我在ConsoleExmpales/Examples/Radial中发现了一些RBF示例，但它看起来不再起作用，因为在Encog中已经更改了一些方法。

到目前为止，我坚持这个：

public static double[][] XORInput = { 
     new[] {0.0, 0.0}, 
     new[] {1.0, 0.0}, 
     new[] {0.0, 1.0}, 
     new[] {1.0, 1.0} 
    }; 

    public static double[][] XORIdeal = { 
     new[] {0.0}, 
     new[] {1.0}, 
     new[] {1.0}, 
     new[] {0.0} 
    }; 

     int dimension = 8; 
     int numNeuronsPerDimension = 64; 
     double volumeNeuronWidth = 2.0/numNeuronsPerDimension; 
     bool includeEdgeRBFs = true; 

     RBFNetwork n = new RBFNetwork(dimension, numNeuronsPerDimension, 1, RBFEnum.Gaussian); 
     n.SetRBFCentersAndWidthsEqualSpacing(0, 1, RBFEnum.Gaussian, volumeNeuronWidth, includeEdgeRBFs); 
     //n.RandomizeRBFCentersAndWidths(0, 1, RBFEnum.Gaussian); 

     INeuralDataSet trainingSet = new BasicNeuralDataSet(XORInput, XORIdeal); 
     SVDTraining train = new SVDTraining(n, trainingSet); 

     int epoch = 1; 
     do 
     { 
      train.Iteration(); 
      Console.WriteLine("Epoch #" + epoch + " Error:" + train.Error); 
      epoch++; 
     } while ((epoch < 1) && (train.Error > 0.001)); 

当我跑，我得到错误“RBF神经元的总数必须有一些整数‘尺寸’的力量。”在SetRBFCentersAndWidthsEqualSpacing。如果我改变这个方法RandomizeRBFCentersAndWidths，直到train.iteration（）到达，我得到“索引是在数组边界之外”。

我了解网络如何RBF工作，但我很困惑在SetRBFCentersAndWidthsEqualSpacing方法的所有参数，有人可以解释更详细？

Answer 1

非常好的问题。

1. SetRBFCentersAndWidthsEqualSpacingand here相对训练神经网络的新的方法和杰夫·希顿决定来实现它。

2. 看起来像在第230-240行的Java version和C# version之间存在差异，并且IMHO错误位于Java版本中。

3. 我修改你的代码，以便它是可行的补充评论：

   using System; 
   using System.Collections.Generic; 
   using System.Linq; 
   using System.Text; 
   using System.Threading.Tasks; 
   using Encog.MathUtil.RBF; 
   using Encog.Neural.Data.Basic; 
   using Encog.Neural.NeuralData; 
   using Encog.Neural.Rbf.Training; 
   using Encog.Neural.RBF; 
   
   namespace TestRBF 
   { 
       class Program 
       { 
        public static double[][] XORInput = { 
        new[] {0.0, 0.0}, 
        new[] {1.0, 0.0}, 
        new[] {0.0, 1.0}, 
        new[] {1.0, 1.0} 
       }; 
   
        public static double[][] XORIdeal = { 
        new[] {0.0}, 
        new[] {1.0}, 
        new[] {1.0}, 
        new[] {0.0} 
       }; 
   
        static void Main(string[] args) 
        { 
         int dimension = 2; // XORInput provides two-dimensional inputs. Not 8. 
         /* 
         If XORInput is 8 dimensional it should be like this: 
   
         public static double[][] XORInput = { 
         new[] {0.0, 0.0,0.0, 0.0,0.0, 0.0,0.0, 0.0}, 
         . 
         . 
         .*/ 
         int numNeuronsPerDimension = 4; // could be also 16, 64, 256. I suppose it should accept 8, 32 but it needs additional investigation 
         double volumeNeuronWidth = 2.0/numNeuronsPerDimension; 
         bool includeEdgeRBFs = true; 
   
         RBFNetwork n = new RBFNetwork(dimension, numNeuronsPerDimension, 1, RBFEnum.Gaussian); 
         n.SetRBFCentersAndWidthsEqualSpacing(0, 1, RBFEnum.Gaussian, volumeNeuronWidth, includeEdgeRBFs); 
         //n.RandomizeRBFCentersAndWidths(0, 1, RBFEnum.Gaussian); 
   
         INeuralDataSet trainingSet = new BasicNeuralDataSet(XORInput, XORIdeal); 
         SVDTraining train = new SVDTraining(n, trainingSet); 
   
         int epoch = 1; 
         do 
         { 
          train.Iteration(); 
          Console.WriteLine("Epoch #" + epoch + " Error:" + train.Error); 
          epoch++; 
         } while ((epoch < 1) && (train.Error > 0.001)); 
   
        } 
       } 
   }