Changeset 8664 for trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/SymbolicRegressionMultiObjectiveTrainingBestSolutionAnalyzer.cs
- Timestamp:
- 09/17/12 11:18:40 (12 years ago)
- File:
-
- 1 edited
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trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/SymbolicRegressionMultiObjectiveTrainingBestSolutionAnalyzer.cs
r7259 r8664 22 22 using HeuristicLab.Common; 23 23 using HeuristicLab.Core; 24 using HeuristicLab.Data;25 24 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding; 26 25 using HeuristicLab.Parameters; … … 38 37 private const string SymbolicDataAnalysisTreeInterpreterParameterName = "SymbolicDataAnalysisTreeInterpreter"; 39 38 private const string EstimationLimitsParameterName = "EstimationLimits"; 40 private const string ApplyLinearScalingParameterName = "ApplyLinearScaling";41 39 #region parameter properties 42 40 public ILookupParameter<IRegressionProblemData> ProblemDataParameter { … … 48 46 public IValueLookupParameter<DoubleLimit> EstimationLimitsParameter { 49 47 get { return (IValueLookupParameter<DoubleLimit>)Parameters[EstimationLimitsParameterName]; } 50 }51 public IValueParameter<BoolValue> ApplyLinearScalingParameter {52 get { return (IValueParameter<BoolValue>)Parameters[ApplyLinearScalingParameterName]; }53 }54 #endregion55 56 #region properties57 public BoolValue ApplyLinearScaling {58 get { return ApplyLinearScalingParameter.Value; }59 48 } 60 49 #endregion … … 68 57 Parameters.Add(new LookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>(SymbolicDataAnalysisTreeInterpreterParameterName, "The symbolic data analysis tree interpreter for the symbolic expression tree.")); 69 58 Parameters.Add(new ValueLookupParameter<DoubleLimit>(EstimationLimitsParameterName, "The lower and upper limit for the estimated values produced by the symbolic regression model.")); 70 Parameters.Add(new ValueParameter<BoolValue>(ApplyLinearScalingParameterName, "Flag that indicates if the produced symbolic regression solution should be linearly scaled.", new BoolValue(true)));71 59 } 72 60 … … 77 65 protected override ISymbolicRegressionSolution CreateSolution(ISymbolicExpressionTree bestTree, double[] bestQuality) { 78 66 var model = new SymbolicRegressionModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper); 79 if (ApplyLinearScaling.Value) 80 SymbolicRegressionModel.Scale(model, ProblemDataParameter.ActualValue); 67 if (ApplyLinearScalingParameter.ActualValue.Value) SymbolicRegressionModel.Scale(model, ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TargetVariable); 81 68 return new SymbolicRegressionSolution(model, (IRegressionProblemData)ProblemDataParameter.ActualValue.Clone()); 82 69 }
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