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Changeset 8972 for trunk


Ignore:
Timestamp:
11/29/12 10:59:55 (12 years ago)
Author:
mkommend
Message:

#1951: Changed SymbolicDataAnalysisModel.Scale to a protected instance method, added the method in the classificaton and regression models and adapted all calls to the Scale method.

Location:
trunk/sources
Files:
23 edited

Legend:

Unmodified
Added
Removed

  • trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/Interfaces/ISymbolicClassificationModel.cs

    r8594 r8972  
    2727    void RecalculateModelParameters(IClassificationProblemData problemData, IEnumerable<int> rows);
    2828    new ISymbolicClassificationSolution CreateClassificationSolution(IClassificationProblemData problemData);
     29
     30    void Scale(IClassificationProblemData problemData);
    2931  }
    3032}

  • trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/MultiObjective/SymbolicClassificationMultiObjectiveTrainingBestSolutionAnalyzer.cs

    r8883 r8972  
    8282    protected override ISymbolicClassificationSolution CreateSolution(ISymbolicExpressionTree bestTree, double[] bestQuality) {
    8383      var model = ModelCreatorParameter.ActualValue.CreateSymbolicClassificationModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
    84       if (ApplyLinearScalingParameter.ActualValue.Value) SymbolicClassificationModel.Scale(model, ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TargetVariable);
     84      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
    8585
    8686      model.RecalculateModelParameters(ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TrainingIndices);

  • trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/MultiObjective/SymbolicClassificationMultiObjectiveValidationBestSolutionAnalyzer.cs

    r8883 r8972  
    7272    protected override ISymbolicClassificationSolution CreateSolution(ISymbolicExpressionTree bestTree, double[] bestQualities) {
    7373      var model = ModelCreatorParameter.ActualValue.CreateSymbolicClassificationModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
    74       if (ApplyLinearScalingParameter.ActualValue.Value) SymbolicClassificationModel.Scale(model, ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TargetVariable);
     74      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
    7575
    7676      model.RecalculateModelParameters(ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TrainingIndices);

  • trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectivePenaltyScoreEvaluator.cs

    r8883 r8972  
    9292
    9393      var model = ModelCreatorParameter.ActualValue.CreateSymbolicClassificationModel(tree, SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
    94       if (ApplyLinearScalingParameter.ActualValue.Value) SymbolicClassificationModel.Scale(model, problemData, problemData.TargetVariable);
     94      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(problemData);
    9595      model.RecalculateModelParameters(problemData, rows);
    9696      double penalty = Calculate(model, problemData, rows);

  • trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveTrainingBestSolutionAnalyzer.cs

    r8883 r8972  
    8282    protected override ISymbolicClassificationSolution CreateSolution(ISymbolicExpressionTree bestTree, double bestQuality) {
    8383      var model = ModelCreatorParameter.ActualValue.CreateSymbolicClassificationModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
    84       if (ApplyLinearScalingParameter.ActualValue.Value) SymbolicClassificationModel.Scale(model, ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TargetVariable);
     84      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
    8585
    8686      model.RecalculateModelParameters(ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TrainingIndices);

  • trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveTrainingParetoBestSolutionAnalyzer.cs

    r8883 r8972  
    6565    protected override ISymbolicClassificationSolution CreateSolution(ISymbolicExpressionTree bestTree) {
    6666      var model = ModelCreatorParameter.ActualValue.CreateSymbolicClassificationModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
    67       if (ApplyLinearScalingParameter.ActualValue.Value) SymbolicClassificationModel.Scale(model, ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TargetVariable);
     67      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
    6868
    6969      model.RecalculateModelParameters(ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TrainingIndices);

  • trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveValidationBestSolutionAnalyzer.cs

    r8883 r8972  
    7272    protected override ISymbolicClassificationSolution CreateSolution(ISymbolicExpressionTree bestTree, double bestQuality) {
    7373      var model = ModelCreatorParameter.ActualValue.CreateSymbolicClassificationModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
    74       if (ApplyLinearScalingParameter.ActualValue.Value) SymbolicClassificationModel.Scale(model, ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TargetVariable);
     74      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
    7575
    7676      model.RecalculateModelParameters(ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TrainingIndices);

  • trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveValidationParetoBestSolutionAnalyzer.cs

    r8883 r8972  
    6565    protected override ISymbolicClassificationSolution CreateSolution(ISymbolicExpressionTree bestTree) {
    6666      var model = ModelCreatorParameter.ActualValue.CreateSymbolicClassificationModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
    67       if (ApplyLinearScalingParameter.ActualValue.Value) SymbolicClassificationModel.Scale(model, ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TargetVariable);
     67      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
    6868
    6969      model.RecalculateModelParameters(ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TrainingIndices);

  • trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationModel.cs

    r8664 r8972  
    6262      return CreateClassificationSolution(problemData);
    6363    }
     64
     65    public void Scale(IClassificationProblemData problemData) {
     66      Scale(problemData, problemData.TargetVariable);
     67    }
    6468  }
    6569}

  • trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression.Views/3.4/InteractiveSymbolicRegressionSolutionSimplifierView.cs

    r8946 r8972  
    4444    protected override void UpdateModel(ISymbolicExpressionTree tree) {
    4545      var model = new SymbolicRegressionModel(tree, Content.Model.Interpreter, Content.Model.LowerEstimationLimit, Content.Model.UpperEstimationLimit);
    46       SymbolicRegressionModel.Scale(model, Content.ProblemData, Content.ProblemData.TargetVariable);
     46      model.Scale(Content.ProblemData);
    4747      Content.Model = model;
    4848    }

  • trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/Interfaces/ISymbolicRegressionModel.cs

    r8584 r8972  
    2424    double LowerEstimationLimit { get; }
    2525    double UpperEstimationLimit { get; }
     26
     27    void Scale(IRegressionProblemData problemData);
    2628  }
    2729}

  • trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/SymbolicRegressionMultiObjectiveTrainingBestSolutionAnalyzer.cs

    r8664 r8972  
    6565    protected override ISymbolicRegressionSolution CreateSolution(ISymbolicExpressionTree bestTree, double[] bestQuality) {
    6666      var model = new SymbolicRegressionModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
    67       if (ApplyLinearScalingParameter.ActualValue.Value) SymbolicRegressionModel.Scale(model, ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TargetVariable);
     67      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
    6868      return new SymbolicRegressionSolution(model, (IRegressionProblemData)ProblemDataParameter.ActualValue.Clone());
    6969    }

  • trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/SymbolicRegressionMultiObjectiveValidationBestSolutionAnalyzer.cs

    r8664 r8972  
    5555    protected override ISymbolicRegressionSolution CreateSolution(ISymbolicExpressionTree bestTree, double[] bestQuality) {
    5656      var model = new SymbolicRegressionModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
    57       if (ApplyLinearScalingParameter.ActualValue.Value) SymbolicRegressionModel.Scale(model, ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TargetVariable);
     57      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
    5858      return new SymbolicRegressionSolution(model, (IRegressionProblemData)ProblemDataParameter.ActualValue.Clone());
    5959    }

  • trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveTrainingBestSolutionAnalyzer.cs

    r8664 r8972  
    6464    protected override ISymbolicRegressionSolution CreateSolution(ISymbolicExpressionTree bestTree, double bestQuality) {
    6565      var model = new SymbolicRegressionModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
    66       if (ApplyLinearScalingParameter.ActualValue.Value) SymbolicRegressionModel.Scale(model, ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TargetVariable);
     66      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
    6767      return new SymbolicRegressionSolution(model, (IRegressionProblemData)ProblemDataParameter.ActualValue.Clone());
    6868    }

  • trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveTrainingParetoBestSolutionAnalyzer.cs

    r8664 r8972  
    4343    protected override ISymbolicRegressionSolution CreateSolution(ISymbolicExpressionTree bestTree) {
    4444      var model = new SymbolicRegressionModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
    45       if (ApplyLinearScalingParameter.ActualValue.Value) SymbolicRegressionModel.Scale(model, ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TargetVariable);
     45      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
    4646      return new SymbolicRegressionSolution(model, (IRegressionProblemData)ProblemDataParameter.ActualValue.Clone());
    4747    }

  • trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveValidationBestSolutionAnalyzer.cs

    r8664 r8972  
    5656    protected override ISymbolicRegressionSolution CreateSolution(ISymbolicExpressionTree bestTree, double bestQuality) {
    5757      var model = new SymbolicRegressionModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
    58       if (ApplyLinearScalingParameter.ActualValue.Value) SymbolicRegressionModel.Scale(model, ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TargetVariable);
     58      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
    5959      return new SymbolicRegressionSolution(model, (IRegressionProblemData)ProblemDataParameter.ActualValue.Clone());
    6060    }

  • trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveValidationParetoBestSolutionAnalyzer.cs

    r8664 r8972  
    4343    protected override ISymbolicRegressionSolution CreateSolution(ISymbolicExpressionTree bestTree) {
    4444      var model = new SymbolicRegressionModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
    45       if (ApplyLinearScalingParameter.ActualValue.Value) SymbolicRegressionModel.Scale(model, ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TargetVariable);
     45      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
    4646      return new SymbolicRegressionSolution(model, (IRegressionProblemData)ProblemDataParameter.ActualValue.Clone());
    4747    }

  • trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SymbolicRegressionModel.cs

    r8664 r8972  
    6969      return CreateRegressionSolution(problemData);
    7070    }
     71
     72    public void Scale(IRegressionProblemData problemData) {
     73      Scale(problemData, problemData.TargetVariable);
     74    }
    7175  }
    7276}

  • trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis.Views/3.4/InteractiveSymbolicTimeSeriesPrognosisSolutionSimplifierView.cs

    r8798 r8972  
    5151    protected override void UpdateModel(ISymbolicExpressionTree tree) {
    5252      var model = new SymbolicTimeSeriesPrognosisModel(tree, Content.Model.Interpreter);
    53       SymbolicTimeSeriesPrognosisModel.Scale(model, Content.ProblemData, Content.ProblemData.TargetVariable);
     53      model.Scale(Content.ProblemData);
    5454      Content.Model = model;
    5555    }

  • trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SingleObjective/SymbolicTimeSeriesPrognosisSingleObjectiveMeanSquaredErrorEvaluator.cs

    r8798 r8972  
    7373      } else if (applyLinearScaling) { //first create model to perform linear scaling and afterwards calculate fitness for the scaled model
    7474        var model = new SymbolicTimeSeriesPrognosisModel((ISymbolicExpressionTree)solution.Clone(), interpreter, lowerEstimationLimit, upperEstimationLimit);
    75         SymbolicTimeSeriesPrognosisModel.Scale(model, problemData, problemData.TargetVariable);
     75        model.Scale(problemData);
    7676        var scaledSolution = model.SymbolicExpressionTree;
    7777        estimatedValues = interpreter.GetSymbolicExpressionTreeValues(scaledSolution, problemData.Dataset, rows, horizions).SelectMany(x => x);

  • trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SingleObjective/SymbolicTimeSeriesPrognosisSingleObjectiveTrainingBestSolutionAnalyzer.cs

    r8798 r8972  
    6565    protected override ISymbolicTimeSeriesPrognosisSolution CreateSolution(ISymbolicExpressionTree bestTree, double bestQuality) {
    6666      var model = new SymbolicTimeSeriesPrognosisModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue as ISymbolicTimeSeriesPrognosisExpressionTreeInterpreter, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
    67       if (ApplyLinearScalingParameter.ActualValue.Value) SymbolicTimeSeriesPrognosisModel.Scale(model, ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TargetVariable);
     67      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
    6868      return new SymbolicTimeSeriesPrognosisSolution(model, (ITimeSeriesPrognosisProblemData)ProblemDataParameter.ActualValue.Clone());
    6969    }

  • trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SingleObjective/SymbolicTimeSeriesPrognosisSingleObjectiveValidationBestSolutionAnalyzer.cs

    r8798 r8972  
    5353    protected override ISymbolicTimeSeriesPrognosisSolution CreateSolution(ISymbolicExpressionTree bestTree, double bestQuality) {
    5454      var model = new SymbolicTimeSeriesPrognosisModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue as ISymbolicTimeSeriesPrognosisExpressionTreeInterpreter, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
    55       if (ApplyLinearScalingParameter.ActualValue.Value) SymbolicTimeSeriesPrognosisModel.Scale(model, ProblemDataParameter.ActualValue, ProblemDataParameter.ActualValue.TargetVariable);
     55      if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue);
    5656
    5757      return new SymbolicTimeSeriesPrognosisSolution(model, (ITimeSeriesPrognosisProblemData)ProblemDataParameter.ActualValue.Clone());

  • trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/SymbolicDataAnalysisModel.cs

    r8664 r8972  
    6969
    7070    #region Scaling
    71     public static void Scale(ISymbolicDataAnalysisModel model, IDataAnalysisProblemData problemData, string targetVariable) {
     71    protected void Scale(IDataAnalysisProblemData problemData, string targetVariable) {
    7272      var dataset = problemData.Dataset;
    7373      var rows = problemData.TrainingIndices;
    74       var estimatedValues = model.Interpreter.GetSymbolicExpressionTreeValues(model.SymbolicExpressionTree, dataset, rows);
     74      var estimatedValues = Interpreter.GetSymbolicExpressionTreeValues(SymbolicExpressionTree, dataset, rows);
    7575      var targetValues = dataset.GetDoubleValues(targetVariable, rows);
    7676
    … …  
    9494      ConstantTreeNode betaTreeNode = null;
    9595      // check if model has been scaled previously by analyzing the structure of the tree
    96       var startNode = model.SymbolicExpressionTree.Root.GetSubtree(0);
     96      var startNode = SymbolicExpressionTree.Root.GetSubtree(0);
    9797      if (startNode.GetSubtree(0).Symbol is Addition) {
    9898        var addNode = startNode.GetSubtree(0);
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