C# (CSharp) HeuristicLab.Algorithms.DataAnalysis NeuralNetworkModel Examples

Example #1

File: NeuralNetworkModel.cs Project: t-h-e/HeuristicLab

 private NeuralNetworkModel(NeuralNetworkModel original, Cloner cloner)
   : base(original, cloner) {
   multiLayerPerceptron = new alglib.multilayerperceptron();
   multiLayerPerceptron.innerobj.chunks = (double[,])original.multiLayerPerceptron.innerobj.chunks.Clone();
   multiLayerPerceptron.innerobj.columnmeans = (double[])original.multiLayerPerceptron.innerobj.columnmeans.Clone();
   multiLayerPerceptron.innerobj.columnsigmas = (double[])original.multiLayerPerceptron.innerobj.columnsigmas.Clone();
   multiLayerPerceptron.innerobj.derror = (double[])original.multiLayerPerceptron.innerobj.derror.Clone();
   multiLayerPerceptron.innerobj.dfdnet = (double[])original.multiLayerPerceptron.innerobj.dfdnet.Clone();
   multiLayerPerceptron.innerobj.neurons = (double[])original.multiLayerPerceptron.innerobj.neurons.Clone();
   multiLayerPerceptron.innerobj.nwbuf = (double[])original.multiLayerPerceptron.innerobj.nwbuf.Clone();
   multiLayerPerceptron.innerobj.structinfo = (int[])original.multiLayerPerceptron.innerobj.structinfo.Clone();
   multiLayerPerceptron.innerobj.weights = (double[])original.multiLayerPerceptron.innerobj.weights.Clone();
   multiLayerPerceptron.innerobj.x = (double[])original.multiLayerPerceptron.innerobj.x.Clone();
   multiLayerPerceptron.innerobj.y = (double[])original.multiLayerPerceptron.innerobj.y.Clone();
   allowedInputVariables = (string[])original.allowedInputVariables.Clone();
   if (original.classValues != null)
     this.classValues = (double[])original.classValues.Clone();
 }

Example #2

 private NeuralNetworkModel(NeuralNetworkModel original, Cloner cloner)
     : base(original, cloner)
 {
     multiLayerPerceptron = new alglib.multilayerperceptron();
     multiLayerPerceptron.innerobj.chunks       = (double[, ])original.multiLayerPerceptron.innerobj.chunks.Clone();
     multiLayerPerceptron.innerobj.columnmeans  = (double[])original.multiLayerPerceptron.innerobj.columnmeans.Clone();
     multiLayerPerceptron.innerobj.columnsigmas = (double[])original.multiLayerPerceptron.innerobj.columnsigmas.Clone();
     multiLayerPerceptron.innerobj.derror       = (double[])original.multiLayerPerceptron.innerobj.derror.Clone();
     multiLayerPerceptron.innerobj.dfdnet       = (double[])original.multiLayerPerceptron.innerobj.dfdnet.Clone();
     multiLayerPerceptron.innerobj.neurons      = (double[])original.multiLayerPerceptron.innerobj.neurons.Clone();
     multiLayerPerceptron.innerobj.nwbuf        = (double[])original.multiLayerPerceptron.innerobj.nwbuf.Clone();
     multiLayerPerceptron.innerobj.structinfo   = (int[])original.multiLayerPerceptron.innerobj.structinfo.Clone();
     multiLayerPerceptron.innerobj.weights      = (double[])original.multiLayerPerceptron.innerobj.weights.Clone();
     multiLayerPerceptron.innerobj.x            = (double[])original.multiLayerPerceptron.innerobj.x.Clone();
     multiLayerPerceptron.innerobj.y            = (double[])original.multiLayerPerceptron.innerobj.y.Clone();
     allowedInputVariables = (string[])original.allowedInputVariables.Clone();
     if (original.classValues != null)
     {
         this.classValues = (double[])original.classValues.Clone();
     }
 }