Changeset 14887 for branches/RBFRegression/HeuristicLab.Algorithms.DataAnalysis/3.4/KernelRidgeRegression/KernelFunctions/PolysplineKernel.cs

Timestamp:

04/24/17 18:31:44 (7 years ago)

Author:

gkronber

Message:

#2699: worked on kernel ridge regression. moved beta parameter to algorithm. reintroduced IKernel interface to restrict choice of kernel in kernel ridge regression. speed-up by cholesky decomposition and optimization of the calculation of the covariance matrix.

File:

• branches/RBFRegression/HeuristicLab.Algorithms.DataAnalysis/3.4/KernelRidgeRegression/KernelFunctions/PolysplineKernel.cs (modified) (3 diffs)

branches/RBFRegression/HeuristicLab.Algorithms.DataAnalysis/3.4/KernelRidgeRegression/KernelFunctions/PolysplineKernel.cs

@@ -22 +22 @@
 using System;
 using HeuristicLab.Common;
-using HeuristicLab.Core;
-using HeuristicLab.Data;
-using HeuristicLab.Parameters;
+using HeuristicLab.Core;         
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
 
-namespace HeuristicLab.Algorithms.DataAnalysis {
+namespace HeuristicLab.Algorithms.DataAnalysis.KernelRidgeRegression {
   [StorableClass]
-  [Item("PolysplineKernel", "A kernel function that uses the multiquadratic function")]
+  // conditionally positive definite. (need to add polynomials) see http://num.math.uni-goettingen.de/schaback/teaching/sc.pdf 
+  [Item("PolysplineKernel", "A kernel function that uses the poly-spline function ||x-c||^Beta.")]
   public class PolysplineKernel : KernelBase {
 
@@ -40 +39 @@
                 : base(original, cloner) { }
     public PolysplineKernel() {
-      Parameters.Add(new FixedValueParameter<DoubleValue>(BetaParameterName, "The Beta in the kernelfunction ||x-c||^Beta", new DoubleValue(1.5)));
     }
     public override IDeepCloneable Clone(Cloner cloner) {
@@ -48 +46 @@
 
     protected override double Get(double norm) {
-      return Math.Pow(norm, Beta);
+      return Math.Pow(norm, Beta.Value);
     }
 
     protected override double GetGradient(double norm) {
-      return Math.Pow(norm, Beta) * Math.Log(norm);
+      return Math.Pow(norm, Beta.Value) * Math.Log(norm);
     }
   }