Changeset 13300 for trunk/sources
- Timestamp:
- 11/19/15 14:15:19 (9 years ago)
- Location:
- trunk/sources
- Files:
-
- 6 edited
Legend:
- Unmodified
- Added
- Removed
-
trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/PearsonRSquaredNestedTreeSizeEvaluator.cs
r13241 r13300 44 44 public PearsonRSquaredNestedTreeSizeEvaluator() : base() { } 45 45 46 public override IEnumerable<bool> Maximization { get { return new bool[2] { true, false }; } } 46 public override IEnumerable<bool> Maximization { get { return new bool[2] { true, false }; } } // maximize R² & minimize nested tree size 47 47 48 48 public override IOperation InstrumentedApply() { … … 67 67 if (decimalPlaces >= 0) 68 68 r2 = Math.Round(r2, decimalPlaces); 69 return new double[2] { r2, solution.IterateNodesPostfix().Sum(n => n.GetLength()) }; 69 return new double[2] { r2, solution.IterateNodesPostfix().Sum(n => n.GetLength()) }; // sum of the length of the whole sub-tree for each node 70 70 } 71 71 … … 74 74 EstimationLimitsParameter.ExecutionContext = context; 75 75 ApplyLinearScalingParameter.ExecutionContext = context; 76 // DecimalPlaces parameter is a FixedValueParameter and doesn't need the context. 76 77 77 double[] quality = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, tree, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, problemData, rows, ApplyLinearScalingParameter.ActualValue.Value, DecimalPlaces); 78 double[] quality = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, tree, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, problemData, rows, ApplyLinearScalingParameter.ActualValue.Value, DecimalPlaces); 78 79 79 80 SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = null; -
trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/PearsonRSquaredNumberOfVariablesEvaluator.cs
r13241 r13300 44 44 public PearsonRSquaredNumberOfVariablesEvaluator() : base() { } 45 45 46 public override IEnumerable<bool> Maximization { get { return new bool[2] { true, false }; } } 46 public override IEnumerable<bool> Maximization { get { return new bool[2] { true, false }; } } // maximize R² and minimize the number of variables 47 47 48 48 public override IOperation InstrumentedApply() { … … 66 66 if (decimalPlaces >= 0) 67 67 r2 = Math.Round(r2, decimalPlaces); 68 return new double[2] { r2, solution.IterateNodesPostfix().OfType<VariableTreeNode>().Count() }; 68 return new double[2] { r2, solution.IterateNodesPostfix().OfType<VariableTreeNode>().Count() }; // count the number of variables 69 69 } 70 70 … … 73 73 EstimationLimitsParameter.ExecutionContext = context; 74 74 ApplyLinearScalingParameter.ExecutionContext = context; 75 // DecimalPlaces parameter is a FixedValueParameter and doesn't need the context. 75 76 76 77 double[] quality = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, tree, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, problemData, rows, ApplyLinearScalingParameter.ActualValue.Value, DecimalPlaces); -
trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/PearsonRSquaredTreeComplexityEvaluator.cs
r13241 r13300 43 43 public PearsonRSquaredTreeComplexityEvaluator() : base() { } 44 44 45 public override IEnumerable<bool> Maximization { get { return new bool[2] { true, false }; } } 45 public override IEnumerable<bool> Maximization { get { return new bool[2] { true, false }; } } // maximize R² and minimize model complexity 46 46 47 47 public override IOperation InstrumentedApply() { … … 72 72 EstimationLimitsParameter.ExecutionContext = context; 73 73 ApplyLinearScalingParameter.ExecutionContext = context; 74 // DecimalPlaces parameter is a FixedValueParameter and doesn't need the context. 74 75 75 76 double[] quality = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, tree, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, problemData, rows, ApplyLinearScalingParameter.ActualValue.Value, DecimalPlaces); -
trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators/SymbolicRegressionConstantOptimizationEvaluator.cs
r12509 r13300 164 164 165 165 166 // TODO: swap positions of lowerEstimationLimit and upperEstimationLimit parameters 166 167 public static double OptimizeConstants(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, ISymbolicExpressionTree tree, IRegressionProblemData problemData, 167 168 IEnumerable<int> rows, bool applyLinearScaling, int maxIterations, double upperEstimationLimit = double.MaxValue, double lowerEstimationLimit = double.MinValue, bool updateConstantsInTree = true) { -
trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/SymbolicDataAnalysisExpressionTreeSimplificationOperator.cs
r13241 r13300 28 28 29 29 namespace HeuristicLab.Problems.DataAnalysis.Symbolic { 30 [Item("SymbolicExpressionTreeSimplificationOperator", "Simpl fies symbolic expression trees encoding a mathematical formula.")]30 [Item("SymbolicExpressionTreeSimplificationOperator", "Simplifies symbolic expression trees encoding a mathematical formula.")] 31 31 [StorableClass] 32 32 public class SymbolicDataAnalysisExpressionTreeSimplificationOperator : SingleSuccessorOperator, ISymbolicExpressionTreeOperator { -
trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/SymbolicDataAnalysisModelComplexityCalculator.cs
r13241 r13300 42 42 return 2; 43 43 } 44 case OpCodes.Add: { 45 double complexity = 0; 46 for (int i = 0; i < node.SubtreeCount; i++) { 47 complexity += CalculateComplexity(node.GetSubtree(i)); 48 } 49 return complexity; 50 } 44 case OpCodes.Add: 51 45 case OpCodes.Sub: { 52 46 double complexity = 0; … … 56 50 return complexity; 57 51 } 58 case OpCodes.Mul: { 59 double complexity = 1; 60 for (int i = 0; i < node.SubtreeCount; i++) { 61 var nodeComplexity = CalculateComplexity(node.GetSubtree(i)); 62 complexity *= nodeComplexity + 1; 63 } 64 return complexity; 65 } 52 case OpCodes.Mul: 66 53 case OpCodes.Div: { 67 54 double complexity = 1; … … 72 59 return complexity; 73 60 } 74 case OpCodes.Sin: { 75 double complexity = CalculateComplexity(node.GetSubtree(0)); 76 return Math.Pow(2.0, complexity); 77 } 78 case OpCodes.Cos: { 79 double complexity = CalculateComplexity(node.GetSubtree(0)); 80 return Math.Pow(2.0, complexity); 81 } 82 case OpCodes.Tan: { 83 double complexity = CalculateComplexity(node.GetSubtree(0)); 84 return Math.Pow(2.0, complexity); 85 } 86 case OpCodes.Exp: { 87 double complexity = CalculateComplexity(node.GetSubtree(0)); 88 return Math.Pow(2.0, complexity); 89 } 61 case OpCodes.Sin: 62 case OpCodes.Cos: 63 case OpCodes.Tan: 64 case OpCodes.Exp: 90 65 case OpCodes.Log: { 91 66 double complexity = CalculateComplexity(node.GetSubtree(0)); … … 100 75 return complexity * complexity * complexity; 101 76 } 102 case OpCodes.Power: { 77 case OpCodes.Power: 78 case OpCodes.Root: { 103 79 double complexity = CalculateComplexity(node.GetSubtree(0)); 104 var exponent Node= node.GetSubtree(1) as ConstantTreeNode;105 if (exponent Node!= null) {106 double exp onent = exponentNode.Value;107 if (exp onent < 0) exponent = Math.Abs(exponent);108 if (exp onent < 1) exponent = 1 / exponent;109 return Math.Pow(complexity, Math.Round(exp onent));80 var exponent = node.GetSubtree(1) as ConstantTreeNode; 81 if (exponent != null) { 82 double expVal = exponent.Value; 83 if (expVal < 0) expVal = Math.Abs(expVal); 84 if (expVal < 1) expVal = 1 / expVal; 85 return Math.Pow(complexity, Math.Round(expVal)); 110 86 } 111 87 112 double exponentComplexity = CalculateComplexity(node.GetSubtree(1)); 113 return Math.Pow(complexity, 2 * exponentComplexity); 114 } 115 case OpCodes.Root: { 116 double complexity = CalculateComplexity(node.GetSubtree(0)); 117 var rootNode = node.GetSubtree(1) as ConstantTreeNode; 118 if (rootNode != null) { 119 double root = rootNode.Value; 120 if (root < 0) root = Math.Abs(root); 121 if (root < 1) root = 1 / root; 122 return Math.Pow(complexity, Math.Round(root)); 123 } 124 125 double rootComplexity = CalculateComplexity(node.GetSubtree(1)); 126 return Math.Pow(complexity, 2 * rootComplexity); 88 double expComplexity = CalculateComplexity(node.GetSubtree(1)); 89 return Math.Pow(complexity, 2 * expComplexity); 127 90 } 128 91
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