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source: stable/HeuristicLab.Algorithms.DataAnalysis/3.4/KernelRidgeRegression/KernelFunctions/InverseMultiquadraticKernel.cs @ 15298

Last change on this file since 15298 was 15249, checked in by gkronber, 7 years ago

#2699,#2700
merged r14862, r14863, r14911, r14936, r15156, r15157, r15158, r15164, r15169, r15207:15209, r15225, r15227, r15234, r15248 from trunk to stable

File size: 2.5 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.Persistence.Default.CompositeSerializers.Storable;
26
27namespace HeuristicLab.Algorithms.DataAnalysis {
28  [StorableClass]
29  [Item("InverseMultiquadraticKernel", "A kernel function that uses the inverse multi-quadratic function  1 / sqrt(1+||x-c||²/beta²). Similar to http://crsouza.com/2010/03/17/kernel-functions-for-machine-learning-applications/ with beta as a scaling factor.")]
30  public class InverseMultiquadraticKernel : KernelBase {
31    private const double C = 1.0;
32
33    [StorableConstructor]
34    protected InverseMultiquadraticKernel(bool deserializing) : base(deserializing) { }
35
36    protected InverseMultiquadraticKernel(InverseMultiquadraticKernel original, Cloner cloner) : base(original, cloner) { }
37
38    public InverseMultiquadraticKernel() { }
39
40    public override IDeepCloneable Clone(Cloner cloner) {
41      return new InverseMultiquadraticKernel(this, cloner);
42    }
43
44    protected override double Get(double norm) {
45      if (Beta == null) throw new InvalidOperationException("Can not calculate kernel distance while Beta is null");
46      var beta = Beta.Value;
47      if (Math.Abs(beta) < double.Epsilon) return double.NaN;
48      var d = norm / beta;
49      return 1 / Math.Sqrt(C + d * d);
50    }
51
52    //n²/(b³(n²/b² + C)^1.5)
53    protected override double GetGradient(double norm) {
54      if (Beta == null) throw new InvalidOperationException("Can not calculate kernel distance gradient while Beta is null");
55      var beta = Beta.Value;
56      if (Math.Abs(beta) < double.Epsilon) return double.NaN;
57      var d = norm / beta;
58      return d * d / (beta * Math.Pow(d * d + C, 1.5));
59    }
60  }
61}
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