Changeset 8139 for trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification

Timestamp:

06/27/12 17:34:17 (12 years ago)

Author:

mkommend

Message:

#1722: Renamed indizes to indices in the whole trunk solution.

Location:

trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification

Files:

• ClassificationEnsembleSolution.cs (modified) (2 diffs)
• ClassificationSolution.cs (modified) (1 diff)
• ClassificationSolutionBase.cs (modified) (1 diff)
• DiscriminantFunctionClassificationSolution.cs (modified) (2 diffs)
• DiscriminantFunctionClassificationSolutionBase.cs (modified) (3 diffs)

trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ClassificationEnsembleSolution.cs

@@ -148 +148 @@
     public override IEnumerable<double> EstimatedTrainingClassValues {
       get {
-        var rows = ProblemData.TrainingIndizes;
+        var rows = ProblemData.TrainingIndices;
         var estimatedValuesEnumerators = (from model in Model.Models
                                           select new { Model = model, EstimatedValuesEnumerator = model.GetEstimatedClassValues(ProblemData.Dataset, rows).GetEnumerator() })
@@ -167 +167 @@
     public override IEnumerable<double> EstimatedTestClassValues {
       get {
-        var rows = ProblemData.TestIndizes;
+        var rows = ProblemData.TestIndices;
         var estimatedValuesEnumerators = (from model in Model.Models
                                           select new { Model = model, EstimatedValuesEnumerator = model.GetEstimatedClassValues(ProblemData.Dataset, rows).GetEnumerator() })
                                          .ToList();
-        var rowsEnumerator = ProblemData.TestIndizes.GetEnumerator();
+        var rowsEnumerator = ProblemData.TestIndices.GetEnumerator();
         // aggregate to make sure that MoveNext is called for all enumerators 
         while (rowsEnumerator.MoveNext() & estimatedValuesEnumerators.Select(en => en.EstimatedValuesEnumerator.MoveNext()).Aggregate(true, (acc, b) => acc & b)) {

trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ClassificationSolution.cs

@@ -51 +51 @@
     }
     public override IEnumerable<double> EstimatedTrainingClassValues {
-      get { return GetEstimatedClassValues(ProblemData.TrainingIndizes); }
+      get { return GetEstimatedClassValues(ProblemData.TrainingIndices); }
     }
     public override IEnumerable<double> EstimatedTestClassValues {
-      get { return GetEstimatedClassValues(ProblemData.TestIndizes); }
+      get { return GetEstimatedClassValues(ProblemData.TestIndices); }
     }
 

trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ClassificationSolutionBase.cs

@@ -87 +87 @@
     protected void CalculateResults() {
       double[] estimatedTrainingClassValues = EstimatedTrainingClassValues.ToArray(); // cache values
-      double[] originalTrainingClassValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes).ToArray();
+      double[] originalTrainingClassValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices).ToArray();
       double[] estimatedTestClassValues = EstimatedTestClassValues.ToArray(); // cache values
-      double[] originalTestClassValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndizes).ToArray();
+      double[] originalTestClassValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndices).ToArray();
 
       OnlineCalculatorError errorState;

trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/DiscriminantFunctionClassificationSolution.cs

@@ -59 +59 @@
     }
     public override IEnumerable<double> EstimatedTrainingClassValues {
-      get { return GetEstimatedClassValues(ProblemData.TrainingIndizes); }
+      get { return GetEstimatedClassValues(ProblemData.TrainingIndices); }
     }
     public override IEnumerable<double> EstimatedTestClassValues {
-      get { return GetEstimatedClassValues(ProblemData.TestIndizes); }
+      get { return GetEstimatedClassValues(ProblemData.TestIndices); }
     }
 
@@ -82 +82 @@
     }
     public override IEnumerable<double> EstimatedTrainingValues {
-      get { return GetEstimatedValues(ProblemData.TrainingIndizes); }
+      get { return GetEstimatedValues(ProblemData.TrainingIndices); }
     }
     public override IEnumerable<double> EstimatedTestValues {
-      get { return GetEstimatedValues(ProblemData.TestIndizes); }
+      get { return GetEstimatedValues(ProblemData.TestIndices); }
     }
 

trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/DiscriminantFunctionClassificationSolutionBase.cs

@@ -103 +103 @@
     protected void CalculateRegressionResults() {
       double[] estimatedTrainingValues = EstimatedTrainingValues.ToArray(); // cache values
-      double[] originalTrainingValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes).ToArray();
+      double[] originalTrainingValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices).ToArray();
       double[] estimatedTestValues = EstimatedTestValues.ToArray(); // cache values
-      double[] originalTestValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndizes).ToArray();
+      double[] originalTestValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndices).ToArray();
 
       OnlineCalculatorError errorState;
@@ -140 +140 @@
       double[] classValues;
       double[] thresholds;
-      var targetClassValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes);
+      var targetClassValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices);
       AccuracyMaximizationThresholdCalculator.CalculateThresholds(ProblemData, EstimatedTrainingValues, targetClassValues, out classValues, out thresholds);
 
@@ -149 +149 @@
       double[] classValues;
       double[] thresholds;
-      var targetClassValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes);
+      var targetClassValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices);
       NormalDistributionCutPointsThresholdCalculator.CalculateThresholds(ProblemData, EstimatedTrainingValues, targetClassValues, out classValues, out thresholds);