Changeset 5514 for branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification
- Timestamp:
- 02/18/11 11:32:25 (14 years ago)
- Location:
- branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4
- Files:
-
- 4 edited
Legend:
- Unmodified
- Added
- Removed
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branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/MultiObjective/SymbolicClassificationMultiObjectiveMeanSquaredErrorTreeSizeEvaluator.cs
r5505 r5514 42 42 public SymbolicClassificationMultiObjectiveMeanSquaredErrorTreeSizeEvaluator() : base() { } 43 43 44 public override IEnumerable<bool> Maximization { get { return new bool[2] { false, false }; } } 45 44 46 public override IOperation Apply() { 45 47 IEnumerable<int> rows = GenerateRowsToEvaluate(); 46 double[] qualities = Calculate(Symbolic ExpressionTreeInterpreterParameter.ActualValue, SymbolicExpressionTreeParameter.ActualValue, LowerEstimationLimit.Value, UpperEstimationLimit.Value, ProblemData, rows);48 double[] qualities = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, SymbolicExpressionTreeParameter.ActualValue, LowerEstimationLimit.Value, UpperEstimationLimit.Value, ProblemData, rows); 47 49 QualitiesParameter.ActualValue = new DoubleArray(qualities); 48 50 return base.Apply(); -
branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/MultiObjective/SymbolicClassificationMultiObjectivePearsonRSquaredTreeSizeEvaluator.cs
r5505 r5514 21 21 public SymbolicClassificationMultiObjectivePearsonRSquaredTreeSizeEvaluator() : base() { } 22 22 23 public override IEnumerable<bool> Maximization { get { return new bool[2] { true, false }; } } 24 23 25 public override IOperation Apply() { 24 26 IEnumerable<int> rows = GenerateRowsToEvaluate(); 25 double[] qualities = Calculate(Symbolic ExpressionTreeInterpreterParameter.ActualValue, SymbolicExpressionTreeParameter.ActualValue, LowerEstimationLimit.Value, UpperEstimationLimit.Value, ProblemData, rows);27 double[] qualities = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, SymbolicExpressionTreeParameter.ActualValue, LowerEstimationLimit.Value, UpperEstimationLimit.Value, ProblemData, rows); 26 28 QualitiesParameter.ActualValue = new DoubleArray(qualities); 27 29 return base.Apply(); -
branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveMeanSquaredErrorEvaluator.cs
r5505 r5514 42 42 public SymbolicClassificationSingleObjectiveMeanSquaredErrorEvaluator() : base() { } 43 43 44 public override bool Maximization { get { return false; } } 45 44 46 public override IOperation Apply() { 45 47 IEnumerable<int> rows = GenerateRowsToEvaluate(); 46 double quality = Calculate(Symbolic ExpressionTreeInterpreterParameter.ActualValue, SymbolicExpressionTreeParameter.ActualValue, LowerEstimationLimit.Value, UpperEstimationLimit.Value, ProblemData, rows);48 double quality = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, SymbolicExpressionTreeParameter.ActualValue, LowerEstimationLimit.Value, UpperEstimationLimit.Value, ProblemData, rows); 47 49 QualityParameter.ActualValue = new DoubleValue(quality); 48 50 return base.Apply(); -
branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator.cs
r5505 r5514 42 42 public SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator() : base() { } 43 43 44 public override bool Maximization { get { return true; } } 45 44 46 public override IOperation Apply() { 45 47 IEnumerable<int> rows = GenerateRowsToEvaluate(); 46 double quality = Calculate(Symbolic ExpressionTreeInterpreterParameter.ActualValue, SymbolicExpressionTreeParameter.ActualValue, LowerEstimationLimit.Value, UpperEstimationLimit.Value, ProblemData, rows);48 double quality = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, SymbolicExpressionTreeParameter.ActualValue, LowerEstimationLimit.Value, UpperEstimationLimit.Value, ProblemData, rows); 47 49 QualityParameter.ActualValue = new DoubleValue(quality); 48 50 return base.Apply();
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