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source: branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Analyzers/SymbolicRegressionModelQualityCalculator.cs @ 4857

Last change on this file since 4857 was 4068, checked in by swagner, 14 years ago

Sorted usings and removed unused usings in entire solution (#1094)
File size: 8.8 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 HeuristicLab.Core;
23using HeuristicLab.Data;
24using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
25using HeuristicLab.Operators;
26using HeuristicLab.Parameters;
27using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
28using HeuristicLab.Problems.DataAnalysis.Evaluators;
29using HeuristicLab.Problems.DataAnalysis.Symbolic;
30
31namespace HeuristicLab.Problems.DataAnalysis.Regression.Symbolic.Analyzers {
32  /// <summary>
33  /// "An operator to calculate the quality values of a symbolic regression solution symbolic expression tree encoding."
34  /// </summary>
35  [Item("SymbolicRegressionModelQualityCalculator", "An operator to calculate the quality values of a symbolic regression solution symbolic expression tree encoding.")]
36  [StorableClass]
37  public sealed class SymbolicRegressionModelQualityCalculator : AlgorithmOperator {
38    private const string SymbolicExpressionTreeInterpreterParameterName = "SymbolicExpressionTreeInterpreter";
39    private const string SymbolicExpressionTreeParameterName = "SymbolicExpressionTree";
40    private const string ProblemDataParameterName = "ProblemData";
41    private const string ValuesParameterName = "Values";
42    private const string RSQuaredQualityParameterName = "R-squared";
43    private const string MeanSquaredErrorQualityParameterName = "Mean Squared Error";
44    private const string RelativeErrorQualityParameterName = "Relative Error";
45    private const string SamplesStartParameterName = "SamplesStart";
46    private const string SamplesEndParameterName = "SamplesEnd";
47    private const string UpperEstimationLimitParameterName = "UpperEstimationLimit";
48    private const string LowerEstimationLimitParameterName = "LowerEstimationLimit";
49
50    #region parameter properties
51    public ILookupParameter<SymbolicExpressionTree> SymbolicExpressionTreeParameter {
52      get { return (ILookupParameter<SymbolicExpressionTree>)Parameters[SymbolicExpressionTreeParameterName]; }
53    }
54    public IValueLookupParameter<ISymbolicExpressionTreeInterpreter> SymbolicExpressionTreeInterpreterParameter {
55      get { return (IValueLookupParameter<ISymbolicExpressionTreeInterpreter>)Parameters[SymbolicExpressionTreeInterpreterParameterName]; }
56    }
57    public IValueLookupParameter<DataAnalysisProblemData> ProblemDataParameter {
58      get { return (IValueLookupParameter<DataAnalysisProblemData>)Parameters[ProblemDataParameterName]; }
59    }
60    public IValueLookupParameter<IntValue> SamplesStartParameter {
61      get { return (IValueLookupParameter<IntValue>)Parameters[SamplesStartParameterName]; }
62    }
63    public IValueLookupParameter<IntValue> SamplesEndParameter {
64      get { return (IValueLookupParameter<IntValue>)Parameters[SamplesEndParameterName]; }
65    }
66    public IValueLookupParameter<DoubleValue> UpperEstimationLimitParameter {
67      get { return (IValueLookupParameter<DoubleValue>)Parameters[UpperEstimationLimitParameterName]; }
68    }
69    public IValueLookupParameter<DoubleValue> LowerEstimationLimitParameter {
70      get { return (IValueLookupParameter<DoubleValue>)Parameters[LowerEstimationLimitParameterName]; }
71    }
72    public ILookupParameter<DoubleValue> RSquaredQualityParameter {
73      get { return (ILookupParameter<DoubleValue>)Parameters[RSQuaredQualityParameterName]; }
74    }
75    public ILookupParameter<DoubleValue> AverageRelativeErrorQualityParameter {
76      get { return (ILookupParameter<DoubleValue>)Parameters[RelativeErrorQualityParameterName]; }
77    }
78    public ILookupParameter<DoubleValue> MeanSquaredErrorQualityParameter {
79      get { return (ILookupParameter<DoubleValue>)Parameters[MeanSquaredErrorQualityParameterName]; }
80    }
81    #endregion
82
83    public SymbolicRegressionModelQualityCalculator()
84      : base() {
85      Parameters.Add(new LookupParameter<SymbolicExpressionTree>(SymbolicExpressionTreeParameterName, "The symbolic expression tree to analyze."));
86      Parameters.Add(new ValueLookupParameter<ISymbolicExpressionTreeInterpreter>(SymbolicExpressionTreeInterpreterParameterName, "The interpreter that should be used to calculate the output values of the symbolic expression tree."));
87      Parameters.Add(new ValueLookupParameter<DataAnalysisProblemData>(ProblemDataParameterName, "The problem data containing the input varaibles for the symbolic regression problem."));
88      Parameters.Add(new ValueLookupParameter<IntValue>(SamplesStartParameterName, "The first index of the data set partition on which the model quality values should be calculated."));
89      Parameters.Add(new ValueLookupParameter<IntValue>(SamplesEndParameterName, "The first index of the data set partition on which the model quality values should be calculated."));
90      Parameters.Add(new ValueLookupParameter<DoubleValue>(UpperEstimationLimitParameterName, "The upper limit that should be used as cut off value for the output values of symbolic expression trees."));
91      Parameters.Add(new ValueLookupParameter<DoubleValue>(LowerEstimationLimitParameterName, "The lower limit that should be used as cut off value for the output values of symbolic expression trees."));
92      Parameters.Add(new ValueParameter<DoubleMatrix>(ValuesParameterName, "The matrix of original target values and estimated values of the model."));
93      Parameters.Add(new ValueLookupParameter<DoubleValue>(MeanSquaredErrorQualityParameterName, "The mean squared error value of the output of the model."));
94      Parameters.Add(new ValueLookupParameter<DoubleValue>(RSQuaredQualityParameterName, "The R² correlation coefficient of the output of the model and the original target values."));
95      Parameters.Add(new ValueLookupParameter<DoubleValue>(RelativeErrorQualityParameterName, "The average relative percentage error of the output of the model."));
96
97      #region operator initialization
98      SimpleSymbolicRegressionEvaluator simpleEvaluator = new SimpleSymbolicRegressionEvaluator();
99      SimpleRSquaredEvaluator simpleR2Evalator = new SimpleRSquaredEvaluator();
100      SimpleMeanAbsolutePercentageErrorEvaluator simpleRelErrorEvaluator = new SimpleMeanAbsolutePercentageErrorEvaluator();
101      SimpleMSEEvaluator simpleMseEvaluator = new SimpleMSEEvaluator();
102      Assigner clearValues = new Assigner();
103      #endregion
104
105      #region parameter wiring
106      simpleEvaluator.SymbolicExpressionTreeParameter.ActualName = SymbolicExpressionTreeParameter.Name;
107      simpleEvaluator.RegressionProblemDataParameter.ActualName = ProblemDataParameter.Name;
108      simpleEvaluator.SamplesStartParameter.ActualName = SamplesStartParameter.Name;
109      simpleEvaluator.SamplesEndParameter.ActualName = SamplesEndParameter.Name;
110      simpleEvaluator.LowerEstimationLimitParameter.ActualName = LowerEstimationLimitParameter.Name;
111      simpleEvaluator.UpperEstimationLimitParameter.ActualName = UpperEstimationLimitParameter.Name;
112      simpleEvaluator.SymbolicExpressionTreeInterpreterParameter.ActualName = SymbolicExpressionTreeInterpreterParameter.Name;
113      simpleEvaluator.ValuesParameter.ActualName = ValuesParameterName;
114
115      simpleR2Evalator.ValuesParameter.ActualName = ValuesParameterName;
116      simpleR2Evalator.RSquaredParameter.ActualName = RSquaredQualityParameter.Name;
117
118      simpleMseEvaluator.ValuesParameter.ActualName = ValuesParameterName;
119      simpleMseEvaluator.MeanSquaredErrorParameter.ActualName = MeanSquaredErrorQualityParameter.Name;
120
121      simpleRelErrorEvaluator.ValuesParameter.ActualName = ValuesParameterName;
122      simpleRelErrorEvaluator.AverageRelativeErrorParameter.ActualName = AverageRelativeErrorQualityParameter.Name;
123
124      clearValues.LeftSideParameter.ActualName = ValuesParameterName;
125      clearValues.RightSideParameter.Value = new DoubleMatrix();
126      #endregion
127
128      #region operator graph
129      OperatorGraph.InitialOperator = simpleEvaluator;
130      simpleEvaluator.Successor = simpleR2Evalator;
131      simpleR2Evalator.Successor = simpleRelErrorEvaluator;
132      simpleRelErrorEvaluator.Successor = simpleMseEvaluator;
133      simpleMseEvaluator.Successor = clearValues;
134      clearValues.Successor = null;
135      #endregion
136
137    }
138  }
139}
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