source: trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Evaluators/MultiObjectiveSymbolicRegressionEvaluator.cs @ 4468

Last change on this file since 4468 was 4468, checked in by mkommend, 9 years ago

Preparation for cross validation - removed the test samples from the trainining samples and added ValidationPercentage parameter (ticket #1199).

File size: 7.2 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.Collections.Generic;
23using System.Linq;
24using HeuristicLab.Core;
25using HeuristicLab.Data;
26using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
27using HeuristicLab.Operators;
28using HeuristicLab.Parameters;
29using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
30using HeuristicLab.Problems.DataAnalysis.Symbolic;
31
32namespace HeuristicLab.Problems.DataAnalysis.Regression.Symbolic {
33  [Item("MultiObjectiveSymbolicRegressionEvaluator", "Evaluates a symbolic regression solution.")]
34  [StorableClass]
35  public abstract class MultiObjectiveSymbolicRegressionEvaluator : SingleSuccessorOperator, IMultiObjectiveSymbolicRegressionEvaluator {
36    private const string RandomParameterName = "Random";
37    private const string QualitiesParameterName = "Qualities";
38    private const string SymbolicExpressionTreeInterpreterParameterName = "SymbolicExpressionTreeInterpreter";
39    private const string FunctionTreeParameterName = "FunctionTree";
40    private const string RegressionProblemDataParameterName = "RegressionProblemData";
41    private const string SamplesStartParameterName = "SamplesStart";
42    private const string SamplesEndParameterName = "SamplesEnd";
43    private const string RelativeNumberOfEvaluatedSamplesParameterName = "RelativeNumberOfEvaluatedSamples";
44    #region ISymbolicRegressionEvaluator Members
45
46    public ILookupParameter<DoubleArray> QualitiesParameter {
47      get { return (ILookupParameter<DoubleArray>)Parameters[QualitiesParameterName]; }
48    }
49
50    public ILookupParameter<ISymbolicExpressionTreeInterpreter> SymbolicExpressionTreeInterpreterParameter {
51      get { return (ILookupParameter<ISymbolicExpressionTreeInterpreter>)Parameters[SymbolicExpressionTreeInterpreterParameterName]; }
52    }
53
54    public ILookupParameter<SymbolicExpressionTree> SymbolicExpressionTreeParameter {
55      get { return (ILookupParameter<SymbolicExpressionTree>)Parameters[FunctionTreeParameterName]; }
56    }
57
58    public ILookupParameter<DataAnalysisProblemData> RegressionProblemDataParameter {
59      get { return (ILookupParameter<DataAnalysisProblemData>)Parameters[RegressionProblemDataParameterName]; }
60    }
61
62    public IValueLookupParameter<IntValue> SamplesStartParameter {
63      get { return (IValueLookupParameter<IntValue>)Parameters[SamplesStartParameterName]; }
64    }
65
66    public IValueLookupParameter<IntValue> SamplesEndParameter {
67      get { return (IValueLookupParameter<IntValue>)Parameters[SamplesEndParameterName]; }
68    }
69
70    public IValueParameter<PercentValue> RelativeNumberOfEvaluatedSamplesParameter {
71      get { return (IValueParameter<PercentValue>)Parameters[RelativeNumberOfEvaluatedSamplesParameterName]; }
72    }
73
74    public ILookupParameter<IRandom> RandomParameter {
75      get { return (ILookupParameter<IRandom>)Parameters[RandomParameterName]; }
76    }
77
78    #endregion
79    #region properties
80    public IRandom Random {
81      get { return RandomParameter.ActualValue; }
82    }
83    public ISymbolicExpressionTreeInterpreter SymbolicExpressionTreeInterpreter {
84      get { return SymbolicExpressionTreeInterpreterParameter.ActualValue; }
85    }
86    public SymbolicExpressionTree SymbolicExpressionTree {
87      get { return SymbolicExpressionTreeParameter.ActualValue; }
88    }
89    public DataAnalysisProblemData RegressionProblemData {
90      get { return RegressionProblemDataParameter.ActualValue; }
91    }
92    public IntValue SamplesStart {
93      get { return SamplesStartParameter.ActualValue; }
94    }
95    public IntValue SamplesEnd {
96      get { return SamplesEndParameter.ActualValue; }
97    }
98
99    public PercentValue RelativeNumberOfEvaluatedSamples {
100      get { return RelativeNumberOfEvaluatedSamplesParameter.Value; }
101    }
102    #endregion
103
104    public MultiObjectiveSymbolicRegressionEvaluator()
105      : base() {
106      Parameters.Add(new LookupParameter<IRandom>(RandomParameterName, "The random generator to use."));
107      Parameters.Add(new LookupParameter<DoubleArray>(QualitiesParameterName, "The qualities of the evaluated symbolic regression solution."));
108      Parameters.Add(new LookupParameter<ISymbolicExpressionTreeInterpreter>(SymbolicExpressionTreeInterpreterParameterName, "The interpreter that should be used to calculate the output values of the symbolic expression tree."));
109      Parameters.Add(new LookupParameter<SymbolicExpressionTree>(FunctionTreeParameterName, "The symbolic regression solution encoded as a symbolic expression tree."));
110      Parameters.Add(new LookupParameter<DataAnalysisProblemData>(RegressionProblemDataParameterName, "The problem data on which the symbolic regression solution should be evaluated."));
111      Parameters.Add(new ValueLookupParameter<IntValue>(SamplesStartParameterName, "The start index of the dataset partition on which the symbolic regression solution should be evaluated."));
112      Parameters.Add(new ValueLookupParameter<IntValue>(SamplesEndParameterName, "The end index of the dataset partition on which the symbolic regression solution should be evaluated."));
113      Parameters.Add(new ValueParameter<PercentValue>(RelativeNumberOfEvaluatedSamplesParameterName, "The relative number of samples of the dataset partition, which should be randomly chosen for evaluation between the start and end index.", new PercentValue(1)));
114    }
115
116    [StorableConstructor]
117    protected MultiObjectiveSymbolicRegressionEvaluator(bool deserializing) : base(deserializing) { }
118    [StorableHook(Persistence.Default.CompositeSerializers.Storable.HookType.AfterDeserialization)]
119    private void AfterDeserialization() {
120    }
121
122    public override IOperation Apply() {
123      int seed = Random.Next();
124      IEnumerable<int> rows = SingleObjectiveSymbolicRegressionEvaluator.GenerateRowsToEvaluate(seed, RelativeNumberOfEvaluatedSamples.Value, SamplesStart.Value, SamplesEnd.Value)
125         .Where(i => i < RegressionProblemData.TestSamplesStart.Value || RegressionProblemData.TestSamplesEnd.Value <= i);
126      double[] qualities = Evaluate(SymbolicExpressionTreeInterpreter, SymbolicExpressionTree, RegressionProblemData.Dataset,
127        RegressionProblemData.TargetVariable, rows);
128      QualitiesParameter.ActualValue = new DoubleArray(qualities);
129      return base.Apply();
130    }
131
132
133    protected abstract double[] Evaluate(ISymbolicExpressionTreeInterpreter interpreter,
134      SymbolicExpressionTree solution,
135      Dataset dataset,
136      StringValue targetVariable,
137      IEnumerable<int> rows);
138  }
139}
Note: See TracBrowser for help on using the repository browser.