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source: branches/RBFRegression/HeuristicLab.Algorithms.DataAnalysis/3.4/KernelRidgeRegression/KernelFunctions/ThinPlatePolysplineKernel.cs @ 14891

Last change on this file since 14891 was 14891, checked in by bwerth, 7 years ago

#2699 reworked kenel functions (beta is always a scaling factor now), added LU-Decomposition as a fall-back if Cholesky-decomposition fails

File size: 3.4 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System;
23using HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Data;
26using HeuristicLab.Parameters;
27using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
28
29namespace HeuristicLab.Algorithms.DataAnalysis.KernelRidgeRegression {
30  [StorableClass]
31  // conditionally positive definite. (need to add polynomials) see http://num.math.uni-goettingen.de/schaback/teaching/sc.pdf
32  [Item("ThinPlatePolysplineKernel", "A kernel function that uses the ThinPlatePolyspline function (||x-c||/Beta)^(Degree)*log(||x-c||/Beta) as described in \"Thin-Plate Spline Radial Basis Function Scheme for Advection-Diffusion Problems\" with beta as a scaling parameter.")]
33  public class ThinPlatePolysplineKernel : KernelBase {
34
35    #region Parameternames
36    private const string DegreeParameterName = "Degree";
37    #endregion
38    #region Parameterproperties
39    public IFixedValueParameter<DoubleValue> DegreeParameter
40    {
41      get { return Parameters[DegreeParameterName] as IFixedValueParameter<DoubleValue>; }
42    }
43    #endregion
44    #region Properties
45    public DoubleValue Degree
46    {
47      get { return DegreeParameter.Value; }
48    }
49    #endregion
50
51    #region HLConstructors & Boilerplate
52    [StorableConstructor]
53    protected ThinPlatePolysplineKernel(bool deserializing) : base(deserializing) { }
54    [StorableHook(HookType.AfterDeserialization)]
55    private void AfterDeserialization() { }
56    protected ThinPlatePolysplineKernel(ThinPlatePolysplineKernel original, Cloner cloner) : base(original, cloner) { }
57    public ThinPlatePolysplineKernel() {
58      Parameters.Add(new FixedValueParameter<DoubleValue>(DegreeParameterName, "The degree of the kernel. Needs to be greater than zero.", new DoubleValue(2.0)));
59    }
60    public override IDeepCloneable Clone(Cloner cloner) {
61      return new ThinPlatePolysplineKernel(this, cloner);
62    }
63    #endregion
64
65    protected override double Get(double norm) {
66      var beta = Beta.Value;
67      if (Math.Abs(beta) < double.Epsilon) return double.NaN;
68      var d = norm / beta;
69      if (Math.Abs(d) < double.Epsilon) return 0;
70      return Math.Pow(d, Degree.Value) * Math.Log(d);
71    }
72
73    // (Degree/beta) * (norm/beta)^Degree * log(norm/beta)
74    protected override double GetGradient(double norm) {
75      var beta = Beta.Value;
76      if (Math.Abs(beta) < double.Epsilon) return double.NaN;
77      var d = norm / beta;
78      if (Math.Abs(d) < double.Epsilon) return 0;
79      return Degree.Value / beta * Math.Pow(d, Degree.Value) * Math.Log(d);
80    }
81  }
82}
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