Changeset 8664 for trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/SymbolicRegressionMultiObjectivePearsonRSquaredTreeSizeEvaluator.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/SymbolicRegressionMultiObjectivePearsonRSquaredTreeSizeEvaluator.cs
r7259 r8664 47 47 IEnumerable<int> rows = GenerateRowsToEvaluate(); 48 48 var solution = SymbolicExpressionTreeParameter.ActualValue; 49 double[] qualities = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, solution, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, ProblemDataParameter.ActualValue, rows );49 double[] qualities = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, solution, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, ProblemDataParameter.ActualValue, rows, ApplyLinearScalingParameter.ActualValue.Value); 50 50 QualitiesParameter.ActualValue = new DoubleArray(qualities); 51 51 return base.Apply(); 52 52 } 53 53 54 public static double[] Calculate(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, ISymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, IRegressionProblemData problemData, IEnumerable<int> rows ) {54 public static double[] Calculate(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, ISymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, IRegressionProblemData problemData, IEnumerable<int> rows, bool applyLinearScaling) { 55 55 IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows); 56 IEnumerable<double> originalValues = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, rows);56 IEnumerable<double> targetValues = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, rows); 57 57 OnlineCalculatorError errorState; 58 double r2 = OnlinePearsonsRSquaredCalculator.Calculate(estimatedValues, originalValues, out errorState); 59 if (errorState != OnlineCalculatorError.None) r2 = 0.0; 60 return new double[] { r2, solution.Length }; 58 59 double r2; 60 if (applyLinearScaling) { 61 var r2Calculator = new OnlinePearsonsRSquaredCalculator(); 62 CalculateWithScaling(targetValues, estimatedValues, lowerEstimationLimit, upperEstimationLimit, r2Calculator, problemData.Dataset.Rows); 63 errorState = r2Calculator.ErrorState; 64 r2 = r2Calculator.RSquared; 65 } else { 66 IEnumerable<double> boundedEstimatedValues = estimatedValues.LimitToRange(lowerEstimationLimit, upperEstimationLimit); 67 r2 = OnlinePearsonsRSquaredCalculator.Calculate(targetValues, boundedEstimatedValues, out errorState); 68 } 69 70 if (errorState != OnlineCalculatorError.None) r2 = double.NaN; 71 return new double[2] { r2, solution.Length }; 61 72 } 62 73 … … 64 75 SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = context; 65 76 EstimationLimitsParameter.ExecutionContext = context; 77 ApplyLinearScalingParameter.ExecutionContext = context; 66 78 67 double[] quality = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, tree, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, problemData, rows );79 double[] quality = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, tree, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, problemData, rows, ApplyLinearScalingParameter.ActualValue.Value); 68 80 69 81 SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = null; 70 82 EstimationLimitsParameter.ExecutionContext = null; 83 ApplyLinearScalingParameter.ExecutionContext = null; 71 84 72 85 return quality;
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