Changeset 5437 for trunk/sources

Timestamp:

02/04/11 22:00:45 (14 years ago)

Author:

gkronber

Message:

#1356 added default values for upper and lower estimation limits if they are not specified where necessary.

Location:

trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic

Files:

• Analyzers/FixedValidationBestScaledSymbolicRegressionSolutionAnalyzer.cs (modified) (1 diff)
• Analyzers/SymbolicRegressionModelQualityAnalyzer.cs (modified) (1 diff)
• Analyzers/TrainingBestScaledSymbolicRegressionSolutionAnalyzer.cs (modified) (1 diff)
• Evaluators/MultiObjectiveSymbolicRegressionMeanSquaredErrorEvaluator.cs (modified) (1 diff)
• Evaluators/MultiObjectiveSymbolicRegressionPearsonsRSquaredEvaluator.cs (modified) (1 diff)
• Evaluators/SingleObjectiveSymbolicRegressionEvaluator.cs (modified) (1 diff)

trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Analyzers/FixedValidationBestScaledSymbolicRegressionSolutionAnalyzer.cs

@@ -185 +185 @@
         (!Maximization.Value && bestQuality < BestSolutionQuality.Value);
       if (newBest) {
-        double lowerEstimationLimit = LowerEstimationLimit.Value;
-        double upperEstimationLimit = UpperEstimationLimit.Value;
+        double upperEstimationLimit = UpperEstimationLimit != null ? UpperEstimationLimit.Value : double.PositiveInfinity;
+        double lowerEstimationLimit = LowerEstimationLimit != null ? LowerEstimationLimit.Value : double.NegativeInfinity;
         string targetVariable = ProblemData.TargetVariable.Value;
 

trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Analyzers/SymbolicRegressionModelQualityAnalyzer.cs

@@ -140 +140 @@
 
     public override IOperation Apply() {
+      double upperEstimationLimit = UpperEstimationLimit != null ? UpperEstimationLimit.Value : double.PositiveInfinity;
+      double lowerEstimationLimit = LowerEstimationLimit != null ? LowerEstimationLimit.Value : double.NegativeInfinity;
       Analyze(SymbolicExpressionTreeParameter.ActualValue, SymbolicExpressionTreeInterpreterParameter.ActualValue,
-        UpperEstimationLimit.Value, LowerEstimationLimit.Value, ProblemDataParameter.ActualValue,
+        upperEstimationLimit, lowerEstimationLimit, ProblemDataParameter.ActualValue,
         ResultsParameter.ActualValue);
       return base.Apply();

trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Analyzers/TrainingBestScaledSymbolicRegressionSolutionAnalyzer.cs

@@ -277 +277 @@
         (!Maximization.Value && bestQuality < BestSolutionQuality.Value);
       if (newBest) {
-        double lowerEstimationLimit = LowerEstimationLimit.Value;
-        double upperEstimationLimit = UpperEstimationLimit.Value;
+        double upperEstimationLimit = UpperEstimationLimit != null ? UpperEstimationLimit.Value : double.PositiveInfinity;
+        double lowerEstimationLimit = LowerEstimationLimit != null ? LowerEstimationLimit.Value : double.NegativeInfinity;
         string targetVariable = ProblemData.TargetVariable.Value;
 

trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Evaluators/MultiObjectiveSymbolicRegressionMeanSquaredErrorEvaluator.cs

@@ -69 +69 @@
 
     protected override double[] Evaluate(ISymbolicExpressionTreeInterpreter interpreter, SymbolicExpressionTree solution, Dataset dataset, StringValue targetVariable, IEnumerable<int> rows) {
-      double mse = SymbolicRegressionMeanSquaredErrorEvaluator.Calculate(interpreter, solution, LowerEstimationLimit.Value, UpperEstimationLimit.Value, dataset, targetVariable.Value, rows);
+      double upperEstimationLimit = UpperEstimationLimit != null ? UpperEstimationLimit.Value : double.PositiveInfinity;
+      double lowerEstimationLimit = LowerEstimationLimit != null ? LowerEstimationLimit.Value : double.NegativeInfinity;
+      double mse = SymbolicRegressionMeanSquaredErrorEvaluator.Calculate(interpreter, solution, lowerEstimationLimit, upperEstimationLimit, dataset, targetVariable.Value, rows);
       List<string> vars = new List<string>();
       solution.Root.ForEachNodePostfix(n => {

trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Evaluators/MultiObjectiveSymbolicRegressionPearsonsRSquaredEvaluator.cs

@@ -69 +69 @@
 
     protected override double[] Evaluate(ISymbolicExpressionTreeInterpreter interpreter, SymbolicExpressionTree solution, Dataset dataset, StringValue targetVariable, IEnumerable<int> rows) {
-      double r2 = SymbolicRegressionPearsonsRSquaredEvaluator.Calculate(interpreter, solution, LowerEstimationLimit.Value, UpperEstimationLimit.Value, dataset, targetVariable.Value, rows);
+      double upperEstimationLimit = UpperEstimationLimit != null ? UpperEstimationLimit.Value : double.PositiveInfinity;
+      double lowerEstimationLimit = LowerEstimationLimit != null ? LowerEstimationLimit.Value : double.NegativeInfinity;
+      double r2 = SymbolicRegressionPearsonsRSquaredEvaluator.Calculate(interpreter, solution, lowerEstimationLimit, upperEstimationLimit, dataset, targetVariable.Value, rows);
       List<string> vars = new List<string>();
       solution.Root.ForEachNodePostfix(n => {

trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Evaluators/SingleObjectiveSymbolicRegressionEvaluator.cs

@@ -148 +148 @@
     public override IOperation Apply() {
       int seed = Random.Next();
+      double upperEstimationLimit = UpperEstimationLimit != null ? UpperEstimationLimit.Value : double.PositiveInfinity;
+      double lowerEstimationLimit = LowerEstimationLimit != null ? LowerEstimationLimit.Value : double.NegativeInfinity;
       IEnumerable<int> rows = GenerateRowsToEvaluate(seed, RelativeNumberOfEvaluatedSamples.Value, SamplesStart.Value, SamplesEnd.Value)
           .Where(i => i < RegressionProblemData.TestSamplesStart.Value || RegressionProblemData.TestSamplesEnd.Value <= i);
-      double quality = Evaluate(SymbolicExpressionTreeInterpreter, SymbolicExpressionTree, LowerEstimationLimit.Value, UpperEstimationLimit.Value,
+      double quality = Evaluate(SymbolicExpressionTreeInterpreter, SymbolicExpressionTree, lowerEstimationLimit, upperEstimationLimit,
         RegressionProblemData.Dataset,
         RegressionProblemData.TargetVariable.Value, rows);