Changeset 18132 for trunk/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/NMSEMultiObjectiveConstraintsEvaluator.cs

Timestamp:

12/15/21 11:50:57 (2 years ago)

Author:

gkronber

Message:

#3140: merged r18091:18131 from branch to trunk

Location:

trunk

Files:

• . (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4 (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/NMSEMultiObjectiveConstraintsEvaluator.cs (modified) (6 diffs)

trunk/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/NMSEMultiObjectiveConstraintsEvaluator.cs

@@ -90 +90 @@
       var applyLinearScaling = ApplyLinearScalingParameter.ActualValue.Value;
 
-      if (UseConstantOptimization) {
-        SymbolicRegressionConstantOptimizationEvaluator.OptimizeConstants(interpreter, tree, problemData, rows,
+      if (UseParameterOptimization) {
+        SymbolicRegressionParameterOptimizationEvaluator.OptimizeParameters(interpreter, tree, problemData, rows,
           false,
-          ConstantOptimizationIterations,
-          ConstantOptimizationUpdateVariableWeights,
+          ParameterOptimizationIterations,
+          ParameterOptimizationUpdateVariableWeights,
           estimationLimits.Lower,
           estimationLimits.Upper);
@@ -105 +105 @@
           var scaling = offset.GetSubtree(0);
 
-          //Check if tree contains offset and scaling nodes
+          // Check if tree contains offset and scaling nodes
           if (!(offset.Symbol is Addition) || !(scaling.Symbol is Multiplication))
             throw new ArgumentException($"{ItemName} can only be used with LinearScalingGrammar.");
@@ -115 +115 @@
           var newTree = new SymbolicExpressionTree(rootNode);
 
-          //calculate alpha and beta for scaling
+          // calculate alpha and beta for scaling
           var estimatedValues = interpreter.GetSymbolicExpressionTreeValues(newTree, problemData.Dataset, rows);
 
@@ -122 +122 @@
             out var errorState);
           if (errorState == OnlineCalculatorError.None) {
-            //Set alpha and beta to the scaling nodes from ia grammar
-            var offsetParameter = offset.GetSubtree(1) as ConstantTreeNode;
+            // Set alpha and beta to the scaling nodes from linear scaling grammar
+            var offsetParameter = offset.GetSubtree(1) as NumberTreeNode;
             offsetParameter.Value = alpha;
-            var scalingParameter = scaling.GetSubtree(1) as ConstantTreeNode;
+            var scalingParameter = scaling.GetSubtree(1) as NumberTreeNode;
             scalingParameter.Value = beta;
           }
@@ -162 +162 @@
       double upperEstimationLimit,
       IRegressionProblemData problemData, IEnumerable<int> rows, IBoundsEstimator estimator, int decimalPlaces) {
-      OnlineCalculatorError errorState;
       var estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows);
       var targetValues = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, rows);
@@ -174 +173 @@
 
       var boundedEstimatedValues = estimatedValues.LimitToRange(lowerEstimationLimit, upperEstimationLimit);
-      nmse = OnlineNormalizedMeanSquaredErrorCalculator.Calculate(targetValues, boundedEstimatedValues, out errorState);
+      nmse = OnlineNormalizedMeanSquaredErrorCalculator.Calculate(targetValues, boundedEstimatedValues, out OnlineCalculatorError errorState);
 
       if (errorState != OnlineCalculatorError.None) nmse = 1.0;