Changeset 5275 for branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression/3.3/Symbolic/Evaluators
- Timestamp:
- 01/11/11 15:03:46 (14 years ago)
- Location:
- branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression/3.3/Symbolic/Evaluators
- Files:
-
- 8 edited
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- Added
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branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression/3.3/Symbolic/Evaluators/MultiObjectiveSymbolicVectorRegressionEvaluator.cs
r4401 r5275 32 32 using HeuristicLab.Problems.DataAnalysis.Symbolic; 33 33 using HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression.Symbolic.Interfaces; 34 using HeuristicLab.Common; 34 35 35 36 namespace HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression.Symbolic.Evaluators { … … 42 43 } 43 44 #endregion 44 public MultiObjectiveSymbolicVectorRegressionEvaluator(bool deserializing) : base(deserializing) { } 45 [StorableConstructor] 46 protected MultiObjectiveSymbolicVectorRegressionEvaluator(bool deserializing) : base(deserializing) { } 47 protected MultiObjectiveSymbolicVectorRegressionEvaluator(MultiObjectiveSymbolicVectorRegressionEvaluator original, Cloner cloner) 48 : base(original, cloner) { 49 } 45 50 public MultiObjectiveSymbolicVectorRegressionEvaluator() 46 51 : base() { -
branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression/3.3/Symbolic/Evaluators/PartialDerivativeEvaluator.cs
r4197 r5275 39 39 public class PartialDerivativeEvaluator : SingleObjectiveSymbolicVectorRegressionEvaluator { 40 40 41 public PartialDerivativeEvaluator(bool deserializing) : base(deserializing) { } 41 [StorableConstructor] 42 protected PartialDerivativeEvaluator(bool deserializing) : base(deserializing) { } 43 protected PartialDerivativeEvaluator(PartialDerivativeEvaluator original, Cloner cloner) 44 : base(original, cloner) { 45 } 42 46 public PartialDerivativeEvaluator() 43 47 : base() { 44 48 } 45 49 public override IDeepCloneable Clone(Cloner cloner) { 50 return new PartialDerivativeEvaluator(this, cloner); 51 } 46 52 public override double Evaluate(SymbolicExpressionTree tree, ISymbolicExpressionTreeInterpreter interpreter, MultiVariateDataAnalysisProblemData problemData, IEnumerable<string> targetVariables, IEnumerable<int> rows, DoubleArray lowerEstimationBound, DoubleArray upperEstimationBound) { 47 53 -
branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression/3.3/Symbolic/Evaluators/SingleObjectiveSymbolicVectorRegressionEvaluator.cs
r4401 r5275 32 32 using HeuristicLab.Problems.DataAnalysis.Symbolic; 33 33 using HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression.Symbolic.Interfaces; 34 using HeuristicLab.Common; 34 35 35 36 namespace HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression.Symbolic.Evaluators { … … 42 43 } 43 44 #endregion 44 public SingleObjectiveSymbolicVectorRegressionEvaluator(bool deserializing) : base(deserializing) { } 45 [StorableConstructor] 46 protected SingleObjectiveSymbolicVectorRegressionEvaluator(bool deserializing) : base(deserializing) { } 47 protected SingleObjectiveSymbolicVectorRegressionEvaluator(SingleObjectiveSymbolicVectorRegressionEvaluator original, Cloner cloner) 48 : base(original, cloner) { 49 } 45 50 public SingleObjectiveSymbolicVectorRegressionEvaluator() 46 51 : base() { 47 52 Parameters.Add(new LookupParameter<DoubleValue>(QualityParameterName, "The quality of the symbolic vector regression solution.")); 48 53 } 49 50 54 51 55 public override IOperation Apply() { -
branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression/3.3/Symbolic/Evaluators/SymbolicRegressionNormalizedMeanSquaredErrorEvaluator.cs
r4194 r5275 29 29 using HeuristicLab.Problems.DataAnalysis.Evaluators; 30 30 using HeuristicLab.Problems.DataAnalysis.Symbolic; 31 using HeuristicLab.Common; 31 32 32 33 namespace HeuristicLab.Problems.DataAnalysis.Regression.Symbolic { … … 34 35 [StorableClass] 35 36 public class SymbolicRegressionNormalizedMeanSquaredErrorEvaluator : SingleObjectiveSymbolicRegressionEvaluator { 37 [StorableConstructor] 38 protected SymbolicRegressionNormalizedMeanSquaredErrorEvaluator(bool deserializing) : base(deserializing) { } 39 protected SymbolicRegressionNormalizedMeanSquaredErrorEvaluator(SymbolicRegressionNormalizedMeanSquaredErrorEvaluator original, Cloner cloner) 40 : base(original, cloner) { 41 } 36 42 public SymbolicRegressionNormalizedMeanSquaredErrorEvaluator() 37 43 : base() { 38 44 } 39 45 public override IDeepCloneable Clone(Cloner cloner) { 46 return new SymbolicRegressionNormalizedMeanSquaredErrorEvaluator(this, cloner); 47 } 40 48 public override double Evaluate(ISymbolicExpressionTreeInterpreter interpreter, SymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, Dataset dataset, string targetVariable, IEnumerable<int> rows) { 41 49 double nmse = Calculate(interpreter, solution, lowerEstimationLimit, upperEstimationLimit, dataset, targetVariable, rows); -
branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression/3.3/Symbolic/Evaluators/SymbolicVectorRegressionEvaluator.cs
r4401 r5275 31 31 using HeuristicLab.Problems.DataAnalysis.Regression; 32 32 using HeuristicLab.Problems.DataAnalysis.Symbolic; 33 using HeuristicLab.Common; 33 34 34 35 namespace HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression.Symbolic.Evaluators { … … 105 106 #endregion 106 107 107 public SymbolicVectorRegressionEvaluator(bool deserializing) : base(deserializing) { } 108 [StorableConstructor] 109 protected SymbolicVectorRegressionEvaluator(bool deserializing) : base(deserializing) { } 110 protected SymbolicVectorRegressionEvaluator(SymbolicVectorRegressionEvaluator original, Cloner cloner) 111 : base(original, cloner) { 112 } 108 113 public SymbolicVectorRegressionEvaluator() 109 114 : base() { … … 118 123 Parameters.Add(new ValueParameter<PercentValue>(RelativeNumberOfEvaluatedSamplesParameterName, "The relative number of samples of the dataset partition, which should be randomly chosen for evaluation between the start and end index.", new PercentValue(1))); 119 124 } 120 121 125 public static IEnumerable<int> GenerateRowsToEvaluate(int seed, double relativeAmount, int start, int end) { 122 126 if (end < start) throw new ArgumentException("Start value is larger than end value."); -
branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression/3.3/Symbolic/Evaluators/SymbolicVectorRegressionNormalizedMseEvaluator.cs
r4194 r5275 30 30 using HeuristicLab.Problems.DataAnalysis.Regression.Symbolic; 31 31 using HeuristicLab.Problems.DataAnalysis.Symbolic; 32 using HeuristicLab.Common; 32 33 33 34 namespace HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression.Symbolic.Evaluators { … … 37 38 38 39 39 public SymbolicVectorRegressionNormalizedMseEvaluator(bool deserializing) : base(deserializing) { } 40 [StorableConstructor] 41 protected SymbolicVectorRegressionNormalizedMseEvaluator(bool deserializing) : base(deserializing) { } 42 protected SymbolicVectorRegressionNormalizedMseEvaluator(SymbolicVectorRegressionNormalizedMseEvaluator original, Cloner cloner) 43 : base(original, cloner) { 44 } 40 45 public SymbolicVectorRegressionNormalizedMseEvaluator() 41 46 : base() { 47 } 48 public override IDeepCloneable Clone(Cloner cloner) { 49 return new SymbolicVectorRegressionNormalizedMseEvaluator(this, cloner); 42 50 } 43 51 -
branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression/3.3/Symbolic/Evaluators/SymbolicVectorRegressionScaledMseEvaluator.cs
r4194 r5275 30 30 using HeuristicLab.Problems.DataAnalysis.Regression.Symbolic; 31 31 using HeuristicLab.Problems.DataAnalysis.Symbolic; 32 using HeuristicLab.Common; 32 33 33 34 namespace HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression.Symbolic.Evaluators { … … 48 49 #endregion 49 50 51 [StorableConstructor] 52 protected SymbolicVectorRegressionScaledMseEvaluator(bool deserializing) : base(deserializing) { } 53 protected SymbolicVectorRegressionScaledMseEvaluator(SymbolicVectorRegressionScaledMseEvaluator original, Cloner cloner) 54 : base(original, cloner) { 55 } 50 56 public SymbolicVectorRegressionScaledMseEvaluator() 51 57 : base() { … … 53 59 Parameters.Add(new LookupParameter<DoubleArray>(BetaParameterName, "The beta parameter for linear scaling.")); 54 60 } 55 61 public override IDeepCloneable Clone(Cloner cloner) { 62 return new SymbolicVectorRegressionScaledMseEvaluator(this, cloner); 63 } 56 64 public override double[] Evaluate(SymbolicExpressionTree tree, ISymbolicExpressionTreeInterpreter interpreter, MultiVariateDataAnalysisProblemData problemData, IEnumerable<string> targetVariables, IEnumerable<int> rows, DoubleArray lowerEstimationBound, DoubleArray upperEstimationBound) { 57 65 List<string> targetVariablesList = targetVariables.ToList(); -
branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression/3.3/Symbolic/Evaluators/SymbolicVectorRegressionScaledNormalizedMseEvaluator.cs
r4194 r5275 30 30 using HeuristicLab.Problems.DataAnalysis.Regression.Symbolic; 31 31 using HeuristicLab.Problems.DataAnalysis.Symbolic; 32 using HeuristicLab.Common; 32 33 33 34 namespace HeuristicLab.Problems.DataAnalysis.MultiVariate.Regression.Symbolic.Evaluators { … … 48 49 #endregion 49 50 51 [StorableConstructor] 52 protected SymbolicVectorRegressionScaledNormalizedMseEvaluator(bool deserializing) : base(deserializing) { } 53 protected SymbolicVectorRegressionScaledNormalizedMseEvaluator(SymbolicVectorRegressionScaledNormalizedMseEvaluator original, Cloner cloner) 54 : base(original, cloner) { 55 } 50 56 public SymbolicVectorRegressionScaledNormalizedMseEvaluator() 51 57 : base() { … … 53 59 Parameters.Add(new LookupParameter<DoubleArray>(BetaParameterName, "The beta parameter for linear scaling.")); 54 60 } 55 61 public override IDeepCloneable Clone(Cloner cloner) { 62 return new SymbolicVectorRegressionScaledNormalizedMseEvaluator(this, cloner); 63 } 56 64 public override double Evaluate(SymbolicExpressionTree tree, ISymbolicExpressionTreeInterpreter interpreter, MultiVariateDataAnalysisProblemData problemData, IEnumerable<string> targetVariables, IEnumerable<int> rows, DoubleArray lowerEstimationBound, DoubleArray upperEstimationBound) { 57 65 List<string> targetVariablesList = targetVariables.ToList();
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