Changeset 4250 for trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/SymbolicRegressionProblem.cs
- Timestamp:
- 08/18/10 14:58:56 (14 years ago)
- File:
-
- 1 edited
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trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/SymbolicRegressionProblem.cs
r4128 r4250 21 21 22 22 using System; 23 using System.Collections.Generic;24 23 using System.Linq; 25 24 using HeuristicLab.Common; 26 25 using HeuristicLab.Core; 27 26 using HeuristicLab.Data; 28 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;29 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.Analyzers;30 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.Creators;31 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.Interfaces;32 27 using HeuristicLab.Optimization; 33 28 using HeuristicLab.Parameters; 34 29 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; 35 using HeuristicLab.PluginInfrastructure;36 30 using HeuristicLab.Problems.DataAnalysis.Regression.Symbolic.Analyzers; 37 using HeuristicLab.Problems.DataAnalysis.Symbolic;38 31 39 32 namespace HeuristicLab.Problems.DataAnalysis.Regression.Symbolic { … … 84 77 public SymbolicRegressionProblem() 85 78 : base() { 86 var evaluator = new SymbolicRegression ScaledMeanSquaredErrorEvaluator();87 Parameters.Add(new ValueParameter<BoolValue>("Maximization", "Set to false as the error of the regression model should be minimized.", (BoolValue)new BoolValue( false).AsReadOnly()));79 var evaluator = new SymbolicRegressionPearsonsRSquaredEvaluator(); 80 Parameters.Add(new ValueParameter<BoolValue>("Maximization", "Set to false as the error of the regression model should be minimized.", (BoolValue)new BoolValue(true))); 88 81 Parameters.Add(new ValueParameter<ISymbolicRegressionEvaluator>("Evaluator", "The operator which should be used to evaluate symbolic regression solutions.", evaluator)); 89 82 Parameters.Add(new OptionalValueParameter<DoubleValue>("BestKnownQuality", "The minimal error value that reached by symbolic regression solutions for the problem.")); 90 83 91 evaluator.QualityParameter.ActualName = "Training MeanSquaredError";84 evaluator.QualityParameter.ActualName = "TrainingPearsonR2"; 92 85 93 86 InitializeOperators();
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