Changeset 5722 for branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective
- Timestamp:
- 03/16/11 19:29:57 (14 years ago)
- Location:
- branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective
- Files:
-
- 5 edited
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branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveMeanSquaredErrorEvaluator.cs
r5624 r5722 59 59 60 60 public override double Evaluate(IExecutionContext context, ISymbolicExpressionTree tree, IClassificationProblemData problemData, IEnumerable<int> rows) { 61 return Calculate(SymbolicDataAnalysisTreeInterpreter, tree, LowerEstimationLimit.Value, UpperEstimationLimit.Value, problemData, rows); 61 SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = context; 62 LowerEstimationLimitParameter.ExecutionContext = context; 63 UpperEstimationLimitParameter.ExecutionContext = context; 64 65 double mse = Calculate(SymbolicDataAnalysisTreeInterpreter, tree, LowerEstimationLimit.Value, UpperEstimationLimit.Value, problemData, rows); 66 67 SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = null; 68 LowerEstimationLimitParameter.ExecutionContext = null; 69 UpperEstimationLimitParameter.ExecutionContext = null; 70 71 return mse; 62 72 } 63 73 } -
branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator.cs
r5624 r5722 58 58 59 59 public override double Evaluate(IExecutionContext context, ISymbolicExpressionTree tree, IClassificationProblemData problemData, IEnumerable<int> rows) { 60 return Calculate(SymbolicDataAnalysisTreeInterpreter, tree, LowerEstimationLimit.Value, UpperEstimationLimit.Value, problemData, rows); 60 SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = context; 61 LowerEstimationLimitParameter.ExecutionContext = context; 62 UpperEstimationLimitParameter.ExecutionContext = context; 63 64 double r2 = Calculate(SymbolicDataAnalysisTreeInterpreter, tree, LowerEstimationLimit.Value, UpperEstimationLimit.Value, problemData, rows); 65 66 SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = null; 67 LowerEstimationLimitParameter.ExecutionContext = null; 68 UpperEstimationLimitParameter.ExecutionContext = null; 69 70 return r2; 61 71 } 62 72 } -
branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveProblem.cs
r5720 r5722 70 70 InitializeOperators(); 71 71 UpdateEstimationLimits(); 72 UpdateDatasetPartitions(); 72 73 } 73 74 -
branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveTrainingBestSolutionAnalyzer.cs
r5720 r5722 43 43 private const string UpperEstimationLimitParameterName = "UpperEstimationLimit"; 44 44 private const string LowerEstimationLimitParameterName = "LowerEstimationLimit"; 45 private const string ApplyLinearScalingParameterName = "ApplyLinearScaling"; 45 46 #region parameter properties 46 47 public ILookupParameter<IClassificationProblemData> ProblemDataParameter { … … 56 57 public IValueLookupParameter<DoubleValue> LowerEstimationLimitParameter { 57 58 get { return (IValueLookupParameter<DoubleValue>)Parameters[LowerEstimationLimitParameterName]; } 59 } 60 public IValueParameter<BoolValue> ApplyLinearScalingParameter { 61 get { return (IValueParameter<BoolValue>)Parameters[ApplyLinearScalingParameterName]; } 58 62 } 59 63 #endregion … … 71 75 get { return LowerEstimationLimitParameter.ActualValue; } 72 76 } 77 public BoolValue ApplyLinearScaling { 78 get { return ApplyLinearScalingParameter.Value; } 79 } 73 80 #endregion 74 81 … … 82 89 Parameters.Add(new ValueLookupParameter<DoubleValue>(UpperEstimationLimitParameterName, "The upper limit for the estimated values produced by the symbolic classification model.")); 83 90 Parameters.Add(new ValueLookupParameter<DoubleValue>(LowerEstimationLimitParameterName, "The lower limit for the estimated values produced by the symbolic classification model.")); 91 Parameters.Add(new ValueParameter<BoolValue>(ApplyLinearScalingParameterName, "Flag that indicates if the produced symbolic classification solution should be linearly scaled.", new BoolValue(false))); 84 92 } 85 93 public override IDeepCloneable Clone(Cloner cloner) { -
branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveValidationBestSolutionAnalyzer.cs
r5720 r5722 41 41 private const string UpperEstimationLimitParameterName = "UpperEstimationLimit"; 42 42 private const string LowerEstimationLimitParameterName = "LowerEstimationLimit"; 43 private const string ApplyLinearScalingParameterName = "ApplyLinearScaling"; 43 44 44 45 #region parameter properties … … 49 50 public IValueLookupParameter<DoubleValue> LowerEstimationLimitParameter { 50 51 get { return (IValueLookupParameter<DoubleValue>)Parameters[LowerEstimationLimitParameterName]; } 52 } 53 54 public IValueParameter<BoolValue> ApplyLinearScalingParameter { 55 get { return (IValueParameter<BoolValue>)Parameters[ApplyLinearScalingParameterName]; } 51 56 } 52 57 #endregion … … 59 64 get { return LowerEstimationLimitParameter.ActualValue; } 60 65 } 66 public BoolValue ApplyLinearScaling { 67 get { return ApplyLinearScalingParameter.Value; } 68 } 61 69 #endregion 62 70 [StorableConstructor] … … 67 75 Parameters.Add(new ValueLookupParameter<DoubleValue>(UpperEstimationLimitParameterName, "The upper limit for the estimated values produced by the symbolic classification model.")); 68 76 Parameters.Add(new ValueLookupParameter<DoubleValue>(LowerEstimationLimitParameterName, "The lower limit for the estimated values produced by the symbolic classification model.")); 77 Parameters.Add(new ValueParameter<BoolValue>(ApplyLinearScalingParameterName, "Flag that indicates if the produced symbolic classification solution should be linearly scaled.", new BoolValue(false))); 69 78 } 70 79 public override IDeepCloneable Clone(Cloner cloner) {
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