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source: trunk/sources/HeuristicLab.Problems.DataAnalysis/3.3/SupportVectorMachine/ParameterAdjustmentProblem/SupportVectorMachineParameterAdjustmentEvaluator.cs @ 3884

Last change on this file since 3884 was 3884, checked in by gkronber, 14 years ago

Worked on support vector regression operators and views. #1009

File size: 7.7 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2010 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.Encodings.RealVectorEncoding;
27using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
28using HeuristicLab.Problems.DataAnalysis.SupportVectorMachine;
29using HeuristicLab.Problems.DataAnalysis;
30using HeuristicLab.Problems.DataAnalysis.Evaluators;
31using HeuristicLab.Parameters;
32using HeuristicLab.Optimization;
33using HeuristicLab.Operators;
34
35namespace HeuristicLab.Problems.DataAnalysis.SupportVectorMachine.ParameterAdjustmentProblem {
36  [Item("SupportVectorMachineParameterAdjustmentEvaluator", "")]
37  [StorableClass]
38  public class SupportVectorMachineParameterAdjustmentEvaluator : AlgorithmOperator, ISingleObjectiveEvaluator {
39    private const string ParameterVectorParameterName = "ParameterVector";
40    private const string DataAnalysisProblemDataParameterName = "DataAnalysisProblemData";
41    private const string SvmTypeParameterName = "SvmType";
42    private const string KernelTypeParameterName = "KernelType";
43    private const string CostParameterName = "Cost";
44    private const string NuParameterName = "Nu";
45    private const string GammaParameterName = "Gamma";
46    private const string EpsilonParameterName = "Epsilon";
47    private const string SamplesStartParameterName = "SamplesStart";
48    private const string SamplesEndParameterName = "SamplesEnd";
49    private const string NumberOfFoldsParameterName = "NumberOfFolds";
50    private const string QualityParameterName = "Quality";
51
52    #region parameter properties
53    public ILookupParameter<RealVector> ParameterVectorParameter {
54      get { return (ILookupParameter<RealVector>)Parameters["ParameterVector"]; }
55    }
56    public IValueLookupParameter<DataAnalysisProblemData> DataAnalysisProblemDataParameter {
57      get { return (IValueLookupParameter<DataAnalysisProblemData>)Parameters[DataAnalysisProblemDataParameterName]; }
58    }
59    public IValueLookupParameter<StringValue> SvmTypeParameter {
60      get { return (IValueLookupParameter<StringValue>)Parameters[SvmTypeParameterName]; }
61    }
62    public IValueLookupParameter<StringValue> KernelTypeParameter {
63      get { return (IValueLookupParameter<StringValue>)Parameters[KernelTypeParameterName]; }
64    }
65    public IValueLookupParameter<DoubleValue> NuParameter {
66      get { return (IValueLookupParameter<DoubleValue>)Parameters[NuParameterName]; }
67    }
68    public IValueLookupParameter<DoubleValue> CostParameter {
69      get { return (IValueLookupParameter<DoubleValue>)Parameters[CostParameterName]; }
70    }
71    public IValueLookupParameter<DoubleValue> GammaParameter {
72      get { return (IValueLookupParameter<DoubleValue>)Parameters[GammaParameterName]; }
73    }
74    public IValueLookupParameter<DoubleValue> EpsilonParameter {
75      get { return (IValueLookupParameter<DoubleValue>)Parameters[EpsilonParameterName]; }
76    }
77    public IValueLookupParameter<IntValue> SamplesStartParameter {
78      get { return (IValueLookupParameter<IntValue>)Parameters[SamplesStartParameterName]; }
79    }
80    public IValueLookupParameter<IntValue> SamplesEndParameter {
81      get { return (IValueLookupParameter<IntValue>)Parameters[SamplesEndParameterName]; }
82    }
83    public IValueLookupParameter<IntValue> NumberOfFoldsParameter {
84      get { return (IValueLookupParameter<IntValue>)Parameters[NumberOfFoldsParameterName]; }
85    }
86    public ILookupParameter<DoubleValue> QualityParameter {
87      get { return (ILookupParameter<DoubleValue>)Parameters[QualityParameterName]; }
88    }
89    #endregion
90    #region properties
91    public RealVector ParameterVector {
92      get { return ParameterVectorParameter.ActualValue; }
93    }
94    public DataAnalysisProblemData DataAnalysisProblemData {
95      get { return DataAnalysisProblemDataParameter.ActualValue; }
96    }
97    public StringValue SvmType {
98      get { return SvmTypeParameter.Value; }
99    }
100    public StringValue KernelType {
101      get { return KernelTypeParameter.Value; }
102    }
103    public IntValue SamplesStart {
104      get { return SamplesStartParameter.ActualValue; }
105    }
106    public IntValue SamplesEnd {
107      get { return SamplesEndParameter.ActualValue; }
108    }
109    public IntValue NumberOfFolds {
110      get { return NumberOfFoldsParameter.ActualValue; }
111    }
112    #endregion
113
114    public SupportVectorMachineParameterAdjustmentEvaluator()
115      : base() {
116      StringValue nuSvrType = new StringValue("NU_SVR").AsReadOnly();
117      StringValue rbfKernelType = new StringValue("RBF").AsReadOnly();
118      Parameters.Add(new LookupParameter<RealVector>(ParameterVectorParameterName, "The parameters for the SVM encoded as a real vector."));
119      Parameters.Add(new ValueLookupParameter<DataAnalysisProblemData>(DataAnalysisProblemDataParameterName, "The data analysis problem data to use for training."));
120      Parameters.Add(new ValueLookupParameter<StringValue>(SvmTypeParameterName, "The type of SVM to use.", nuSvrType));
121      Parameters.Add(new ValueLookupParameter<StringValue>(KernelTypeParameterName, "The kernel type to use for the SVM.", rbfKernelType));
122      Parameters.Add(new ValueLookupParameter<DoubleValue>(NuParameterName, "The value of the nu parameter nu-SVC, one-class SVM and nu-SVR."));
123      Parameters.Add(new ValueLookupParameter<DoubleValue>(CostParameterName, "The value of the C (cost) parameter of C-SVC, epsilon-SVR and nu-SVR."));
124      Parameters.Add(new ValueLookupParameter<DoubleValue>(GammaParameterName, "The value of the gamma parameter in the kernel function."));
125      Parameters.Add(new ValueLookupParameter<DoubleValue>(EpsilonParameterName, "The value of the epsilon parameter of epsilon-SVR."));
126      Parameters.Add(new ValueLookupParameter<IntValue>(SamplesStartParameterName, "The first index of the data set partition the support vector machine should use for training."));
127      Parameters.Add(new ValueLookupParameter<IntValue>(SamplesEndParameterName, "The last index of the data set partition the support vector machine should use for training."));
128      Parameters.Add(new ValueLookupParameter<IntValue>(NumberOfFoldsParameterName, "The number of folds to use for cross-validation."));
129      Parameters.Add(new LookupParameter<DoubleValue>(QualityParameterName, "The cross validation quality reached with the given parameters."));
130
131
132      SupportVectorMachineCrossValidationEvaluator evaluator = new SupportVectorMachineCrossValidationEvaluator();
133      OperatorGraph.InitialOperator = evaluator;
134      evaluator.Successor = null;
135    }
136
137    public override IOperation Apply() {
138      var point = ParameterVector;
139      NuParameter.Value = new DoubleValue(point[0]);
140      CostParameter.Value = new DoubleValue(Math.Pow(2, point[1]));
141      GammaParameter.Value = new DoubleValue(Math.Pow(2, point[2]));
142      EpsilonParameter.Value = new DoubleValue();
143      return base.Apply();
144    }
145  }
146}
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