Changeset 4468 for trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Analyzers/SymbolicRegressionModelQualityAnalyzer.cs

Timestamp:

09/22/10 11:22:49 (14 years ago)

Author:

mkommend

Message:

Preparation for cross validation - removed the test samples from the trainining samples and added ValidationPercentage parameter (ticket #1199).

File:

• trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Analyzers/SymbolicRegressionModelQualityAnalyzer.cs (modified) (4 diffs)

trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Analyzers/SymbolicRegressionModelQualityAnalyzer.cs

@@ -137 +137 @@
       Analyze(SymbolicExpressionTreeParameter.ActualValue, SymbolicExpressionTreeInterpreterParameter.ActualValue,
         UpperEstimationLimit.Value, LowerEstimationLimit.Value, ProblemDataParameter.ActualValue,
-        ProblemDataParameter.ActualValue.TrainingSamplesStart.Value, ProblemDataParameter.ActualValue.TrainingSamplesEnd.Value,
-        ProblemDataParameter.ActualValue.TestSamplesStart.Value, ProblemDataParameter.ActualValue.TestSamplesEnd.Value,
         ResultsParameter.ActualValue);
       return base.Apply();
@@ -145 +143 @@
     public static void Analyze(IEnumerable<SymbolicExpressionTree> trees, ISymbolicExpressionTreeInterpreter interpreter,
       double upperEstimationLimit, double lowerEstimationLimit,
-      DataAnalysisProblemData problemData, int trainingStart, int trainingEnd, int testStart, int testEnd, ResultCollection results) {
+      DataAnalysisProblemData problemData, ResultCollection results) {
       int targetVariableIndex = problemData.Dataset.GetVariableIndex(problemData.TargetVariable.Value);
-      IEnumerable<double> originalTrainingValues = problemData.Dataset.GetEnumeratedVariableValues(targetVariableIndex, trainingStart, trainingEnd);
-      IEnumerable<double> originalTestValues = problemData.Dataset.GetEnumeratedVariableValues(targetVariableIndex, testStart, testEnd);
+      IEnumerable<double> originalTrainingValues = problemData.Dataset.GetEnumeratedVariableValues(targetVariableIndex, problemData.TrainingIndizes);
+      IEnumerable<double> originalTestValues = problemData.Dataset.GetEnumeratedVariableValues(targetVariableIndex, problemData.TestIndizes);
       List<double> trainingMse = new List<double>();
       List<double> trainingR2 = new List<double>();
@@ -162 +160 @@
       foreach (var tree in trees) {
         #region training
-        var estimatedTrainingValues = interpreter.GetSymbolicExpressionTreeValues(tree, problemData.Dataset, Enumerable.Range(trainingStart, trainingEnd - trainingStart));
+        var estimatedTrainingValues = interpreter.GetSymbolicExpressionTreeValues(tree, problemData.Dataset, problemData.TrainingIndizes);
         mseEvaluator.Reset();
         r2Evaluator.Reset();
@@ -184 +182 @@
         #endregion
         #region test
-        var estimatedTestValues = interpreter.GetSymbolicExpressionTreeValues(tree, problemData.Dataset, Enumerable.Range(testStart, testEnd - testStart));
+        var estimatedTestValues = interpreter.GetSymbolicExpressionTreeValues(tree, problemData.Dataset, problemData.TestIndizes);
 
         mseEvaluator.Reset();