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Ignore:
Timestamp:
07/05/16 21:34:18 (8 years ago)
Author:
mkommend
Message:

#2584: Merged r13670 and r13916 into stable.
#2609: Merged r13869 and r13900 into stable.

Location:
stable
Files:
9 edited

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Added
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  • stable

  • stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression

  • stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4

  • stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/PearsonRSquaredNestedTreeSizeEvaluator.cs

    r13310 r14004  
    5555
    5656      if (UseConstantOptimization) {
    57         SymbolicRegressionConstantOptimizationEvaluator.OptimizeConstants(interpreter, solution, problemData, rows, applyLinearScaling, ConstantOptimizationIterations, estimationLimits.Upper, estimationLimits.Lower);
     57        SymbolicRegressionConstantOptimizationEvaluator.OptimizeConstants(interpreter, solution, problemData, rows, applyLinearScaling, ConstantOptimizationIterations, updateVariableWeights: ConstantOptimizationUpdateVariableWeights,lowerEstimationLimit: estimationLimits.Lower, upperEstimationLimit: estimationLimits.Upper);
    5858      }
    5959
  • stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/PearsonRSquaredNumberOfVariablesEvaluator.cs

    r13310 r14004  
    5555
    5656      if (UseConstantOptimization) {
    57         SymbolicRegressionConstantOptimizationEvaluator.OptimizeConstants(interpreter, solution, problemData, rows, applyLinearScaling, ConstantOptimizationIterations, estimationLimits.Upper, estimationLimits.Lower);
     57        SymbolicRegressionConstantOptimizationEvaluator.OptimizeConstants(interpreter, solution, problemData, rows, applyLinearScaling, ConstantOptimizationIterations, updateVariableWeights: ConstantOptimizationUpdateVariableWeights, lowerEstimationLimit: estimationLimits.Lower, upperEstimationLimit: estimationLimits.Upper);
    5858      }
    5959      double[] qualities = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, solution, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, ProblemDataParameter.ActualValue, rows, ApplyLinearScalingParameter.ActualValue.Value, DecimalPlaces);
  • stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/PearsonRSquaredTreeComplexityEvaluator.cs

    r13310 r14004  
    5454
    5555      if (UseConstantOptimization) {
    56         SymbolicRegressionConstantOptimizationEvaluator.OptimizeConstants(interpreter, solution, problemData, rows, applyLinearScaling, ConstantOptimizationIterations, estimationLimits.Upper, estimationLimits.Lower);
     56        SymbolicRegressionConstantOptimizationEvaluator.OptimizeConstants(interpreter, solution, problemData, rows, applyLinearScaling, ConstantOptimizationIterations, updateVariableWeights: ConstantOptimizationUpdateVariableWeights, lowerEstimationLimit: estimationLimits.Lower, upperEstimationLimit: estimationLimits.Upper);
    5757      }
    5858      double[] qualities = Calculate(interpreter, solution, estimationLimits.Lower, estimationLimits.Upper, problemData, rows, applyLinearScaling, DecimalPlaces);
  • stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/SymbolicRegressionMultiObjectiveEvaluator.cs

    r13310 r14004  
    3434    private const string ConstantOptimizationIterationsParameterName = "Constant optimization iterations";
    3535
     36    private const string ConstantOptimizationUpdateVariableWeightsParameterName =
     37      "Constant optimization update variable weights";
     38
    3639    public IFixedValueParameter<IntValue> DecimalPlacesParameter {
    3740      get { return (IFixedValueParameter<IntValue>)Parameters[DecimalPlacesParameterName]; }
     
    4548    }
    4649
     50    public IFixedValueParameter<BoolValue> ConstantOptimizationUpdateVariableWeightsParameter {
     51      get { return (IFixedValueParameter<BoolValue>)Parameters[ConstantOptimizationUpdateVariableWeightsParameterName]; }
     52    }
    4753
    4854    public int DecimalPlaces {
     
    5864      set { ConstantOptimizationIterationsParameter.Value.Value = value; }
    5965    }
     66    public bool ConstantOptimizationUpdateVariableWeights {
     67      get { return ConstantOptimizationUpdateVariableWeightsParameter.Value.Value; }
     68      set { ConstantOptimizationUpdateVariableWeightsParameter.Value.Value = value; }
     69    }
    6070
    6171    [StorableConstructor]
     
    7080      Parameters.Add(new FixedValueParameter<BoolValue>(UseConstantOptimizationParameterName, "", new BoolValue(false)));
    7181      Parameters.Add(new FixedValueParameter<IntValue>(ConstantOptimizationIterationsParameterName, "The number of iterations constant optimization should be applied.", new IntValue(5)));
     82      Parameters.Add(new FixedValueParameter<BoolValue>(ConstantOptimizationUpdateVariableWeightsParameterName, "Determines if the variable weights in the tree should be optimized during constant optimization.", new BoolValue(true)) { Hidden = true });
    7283    }
    7384
     
    8394        Parameters.Add(new FixedValueParameter<IntValue>(ConstantOptimizationIterationsParameterName, "The number of iterations constant optimization should be applied.", new IntValue(5)));
    8495      }
     96      if (!Parameters.ContainsKey(ConstantOptimizationUpdateVariableWeightsParameterName)) {
     97        Parameters.Add(new FixedValueParameter<BoolValue>(ConstantOptimizationUpdateVariableWeightsParameterName, "Determines if the variable weights in the tree should be optimized during constant optimization.", new BoolValue(true)));
     98      }
    8599    }
    86100  }
  • stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/SymbolicRegressionMultiObjectiveMeanSquaredErrorTreeSizeEvaluator.cs

    r13310 r14004  
    5454
    5555      if (UseConstantOptimization) {
    56         SymbolicRegressionConstantOptimizationEvaluator.OptimizeConstants(interpreter, solution, problemData, rows, applyLinearScaling, ConstantOptimizationIterations, estimationLimits.Upper, estimationLimits.Lower);
     56        SymbolicRegressionConstantOptimizationEvaluator.OptimizeConstants(interpreter, solution, problemData, rows, applyLinearScaling, ConstantOptimizationIterations, updateVariableWeights: ConstantOptimizationUpdateVariableWeights, lowerEstimationLimit: estimationLimits.Lower, upperEstimationLimit: estimationLimits.Upper);
    5757      }
    5858
  • stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/SymbolicRegressionMultiObjectivePearsonRSquaredTreeSizeEvaluator.cs

    r13310 r14004  
    5454
    5555      if (UseConstantOptimization) {
    56         SymbolicRegressionConstantOptimizationEvaluator.OptimizeConstants(interpreter, solution, problemData, rows, applyLinearScaling, ConstantOptimizationIterations, estimationLimits.Upper, estimationLimits.Lower);
     56        SymbolicRegressionConstantOptimizationEvaluator.OptimizeConstants(interpreter, solution, problemData, rows, applyLinearScaling, ConstantOptimizationIterations, updateVariableWeights: ConstantOptimizationUpdateVariableWeights, lowerEstimationLimit: estimationLimits.Lower, upperEstimationLimit: estimationLimits.Upper);
    5757      }
    5858      double[] qualities = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, solution, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, ProblemDataParameter.ActualValue, rows, ApplyLinearScalingParameter.ActualValue.Value, DecimalPlaces);
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