1 | #region License Information
|
---|
2 | /* HeuristicLab
|
---|
3 | * Copyright (C) 2002-2015 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 |
|
---|
22 | using System.Linq;
|
---|
23 | using HeuristicLab.Common;
|
---|
24 | using HeuristicLab.Core;
|
---|
25 | using HeuristicLab.Data;
|
---|
26 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
|
---|
27 | using HeuristicLab.EvolutionTracking;
|
---|
28 | using HeuristicLab.Optimization;
|
---|
29 | using HeuristicLab.Parameters;
|
---|
30 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
|
---|
31 |
|
---|
32 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
|
---|
33 | [Item("SymbolicDataAnalysisGenealogyAnalyzer", "Genealogy analyzer for symbolic data analysis problems")]
|
---|
34 | [StorableClass]
|
---|
35 | public class SymbolicDataAnalysisGenealogyAnalyzer : GenealogyAnalyzer<ISymbolicExpressionTree> {
|
---|
36 | private const string EvaluatorParameterName = "Evaluator";
|
---|
37 | private const string ProblemDataParameterName = "ProblemData";
|
---|
38 | private const string InterpreterParameterName = "SymbolicExpressionTreeInterpreter";
|
---|
39 | private const string EstimationLimitsParameterName = "EstimationLimits";
|
---|
40 | private const string ApplyLinearScalingParameterName = "ApplyLinearScaling";
|
---|
41 |
|
---|
42 | #region parameters
|
---|
43 | public ILookupParameter<ISingleObjectiveEvaluator> EvaluatorParameter {
|
---|
44 | get {
|
---|
45 | return (ILookupParameter<ISingleObjectiveEvaluator>)Parameters[EvaluatorParameterName];
|
---|
46 | }
|
---|
47 | }
|
---|
48 |
|
---|
49 | public ILookupParameter<IDataAnalysisProblemData> ProblemDataParameter {
|
---|
50 | get {
|
---|
51 | return (ILookupParameter<IDataAnalysisProblemData>)Parameters[ProblemDataParameterName];
|
---|
52 | }
|
---|
53 | }
|
---|
54 |
|
---|
55 | public ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter> InterpreterParameter {
|
---|
56 | get {
|
---|
57 | return (ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>)Parameters[InterpreterParameterName];
|
---|
58 | }
|
---|
59 | }
|
---|
60 |
|
---|
61 | public ILookupParameter<DoubleLimit> EstimationLimitsParameter {
|
---|
62 | get { return (ILookupParameter<DoubleLimit>)Parameters[EstimationLimitsParameterName]; }
|
---|
63 | }
|
---|
64 |
|
---|
65 | public ILookupParameter<BoolValue> ApplyLinearScalingParameter {
|
---|
66 | get { return (ILookupParameter<BoolValue>)Parameters[ApplyLinearScalingParameterName]; }
|
---|
67 | }
|
---|
68 | #endregion
|
---|
69 |
|
---|
70 | public SymbolicDataAnalysisGenealogyAnalyzer() {
|
---|
71 | Parameters.Add(new LookupParameter<ISingleObjectiveEvaluator>(EvaluatorParameterName));
|
---|
72 | Parameters.Add(new LookupParameter<IDataAnalysisProblemData>(ProblemDataParameterName));
|
---|
73 | Parameters.Add(new LookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>(InterpreterParameterName));
|
---|
74 | Parameters.Add(new LookupParameter<DoubleLimit>(EstimationLimitsParameterName));
|
---|
75 | Parameters.Add(new LookupParameter<BoolValue>(ApplyLinearScalingParameterName));
|
---|
76 | }
|
---|
77 |
|
---|
78 | public SymbolicDataAnalysisGenealogyAnalyzer(SymbolicDataAnalysisGenealogyAnalyzer original, Cloner cloner)
|
---|
79 | : base(original, cloner) {
|
---|
80 | }
|
---|
81 |
|
---|
82 | public override IDeepCloneable Clone(Cloner cloner) {
|
---|
83 | return new SymbolicDataAnalysisGenealogyAnalyzer(this, cloner);
|
---|
84 | }
|
---|
85 |
|
---|
86 | [StorableConstructor]
|
---|
87 | protected SymbolicDataAnalysisGenealogyAnalyzer(bool deserializing) : base(deserializing) {
|
---|
88 | }
|
---|
89 |
|
---|
90 | protected override void EvaluateIntermediateChildren() {
|
---|
91 | var results = ResultsParameter.ActualValue;
|
---|
92 | var graph = (IGenealogyGraph<ISymbolicExpressionTree>)results["PopulationGraph"].Value;
|
---|
93 | var population = PopulationParameter.ActualValue;
|
---|
94 | var generation = GenerationsParameter.ActualValue.Value;
|
---|
95 | var problemData = ProblemDataParameter.ActualValue;
|
---|
96 |
|
---|
97 | var vertices = population.Select(graph.GetByContent).Where(x => x.InDegree == 1).Select(x => x.Parents.First());
|
---|
98 | var intermediateVertices = vertices.Where(x => x.Rank.IsAlmost(generation - 0.5));
|
---|
99 |
|
---|
100 | var classificationProblemData = problemData as IClassificationProblemData;
|
---|
101 | var regressionProblemData = problemData as IRegressionProblemData;
|
---|
102 | if (classificationProblemData != null) {
|
---|
103 | var evaluator = (ISymbolicDataAnalysisSingleObjectiveEvaluator<IClassificationProblemData>)EvaluatorParameter.ActualValue;
|
---|
104 | foreach (var v in intermediateVertices) {
|
---|
105 | var child = v.Data;
|
---|
106 | v.Quality = evaluator.Evaluate(this.ExecutionContext, child, classificationProblemData, classificationProblemData.TrainingIndices);
|
---|
107 | }
|
---|
108 | } else if (regressionProblemData != null) {
|
---|
109 | var evaluator = (ISymbolicDataAnalysisSingleObjectiveEvaluator<IRegressionProblemData>)EvaluatorParameter.ActualValue;
|
---|
110 | foreach (var v in intermediateVertices) {
|
---|
111 | var child = v.Data;
|
---|
112 | v.Quality = evaluator.Evaluate(this.ExecutionContext, child, regressionProblemData, problemData.TrainingIndices);
|
---|
113 | }
|
---|
114 | }
|
---|
115 | }
|
---|
116 | }
|
---|
117 | }
|
---|