Changeset 4034 for trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.3/Symbolic

Timestamp:

07/14/10 10:45:41 (14 years ago)

Author:

mkommend

Message:

implemented first version of partially evaluation of samples (ticket #1082)

File:

• trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.3/Symbolic/InteractiveSymbolicRegressionSolutionSimplifierView.cs (modified) (3 diffs)

trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.3/Symbolic/InteractiveSymbolicRegressionSolutionSimplifierView.cs

@@ -91 +91 @@
         root.AddSubTree(start);
         start.AddSubTree(simplifiedExpressionTree.Root);
+        int samplesStart = Content.ProblemData.TrainingSamplesStart.Value;
+        int samplesEnd = Content.ProblemData.TrainingSamplesEnd.Value;
         double originalTrainingMeanSquaredError = SymbolicRegressionMeanSquaredErrorEvaluator.Calculate(
             Content.Model.Interpreter, new SymbolicExpressionTree(root), Content.LowerEstimationLimit, Content.UpperEstimationLimit,
             Content.ProblemData.Dataset, Content.ProblemData.TargetVariable.Value,
-            Content.ProblemData.TrainingSamplesStart.Value, Content.ProblemData.TrainingSamplesEnd.Value);
+            Enumerable.Range(samplesStart, samplesEnd - samplesStart));
 
         this.CalculateReplacementNodes();
@@ -112 +114 @@
       SymbolicExpressionTree tree = new SymbolicExpressionTree(root);
       foreach (SymbolicExpressionTreeNode node in this.simplifiedExpressionTree.IterateNodesPrefix()) {
-        while(start.SubTrees.Count > 0) start.RemoveSubTree(0);
+        while (start.SubTrees.Count > 0) start.RemoveSubTree(0);
         start.AddSubTree(node);
         double constantTreeNodeValue = interpreter.GetSymbolicExpressionTreeValues(tree, Content.ProblemData.Dataset, trainingSamples).Median();
@@ -123 +125 @@
       foreach (SymbolicExpressionTreeNode childNode in currentTreeNode.SubTrees.ToList()) {
         SwitchNode(currentTreeNode, childNode, replacementNodes[childNode]);
+        int samplesStart = Content.ProblemData.TrainingSamplesStart.Value;
+        int samplesEnd = Content.ProblemData.TrainingSamplesEnd.Value;
         double newTrainingMeanSquaredError = SymbolicRegressionMeanSquaredErrorEvaluator.Calculate(
           Content.Model.Interpreter, tree,
           Content.LowerEstimationLimit, Content.UpperEstimationLimit,
           Content.ProblemData.Dataset, Content.ProblemData.TargetVariable.Value,
-          Content.ProblemData.TrainingSamplesStart.Value, Content.ProblemData.TrainingSamplesEnd.Value);
+          Enumerable.Range(samplesStart, samplesEnd - samplesStart));
         nodeImpacts[childNode] = newTrainingMeanSquaredError / originalTrainingMeanSquaredError;
         SwitchNode(currentTreeNode, replacementNodes[childNode], childNode);