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

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/Regression

Files:

• RegressionEnsembleSolution.cs (modified) (2 diffs)
• RegressionSolution.cs (modified) (1 diff)
• RegressionSolutionBase.cs (modified) (5 diffs)

trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Regression/RegressionEnsembleSolution.cs

@@ -153 +153 @@
     public override IEnumerable<double> EstimatedTrainingValues {
       get {
-        var rows = ProblemData.TrainingIndizes;
+        var rows = ProblemData.TrainingIndices;
         var estimatedValuesEnumerators = (from model in Model.Models
                                           select new { Model = model, EstimatedValuesEnumerator = model.GetEstimatedValues(ProblemData.Dataset, rows).GetEnumerator() })
@@ -172 +172 @@
     public override IEnumerable<double> EstimatedTestValues {
       get {
-        var rows = ProblemData.TestIndizes;
+        var rows = ProblemData.TestIndices;
         var estimatedValuesEnumerators = (from model in Model.Models
                                           select new { Model = model, EstimatedValuesEnumerator = model.GetEstimatedValues(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/Regression/RegressionSolution.cs

@@ -55 +55 @@
     }
     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/Regression/RegressionSolutionBase.cs

@@ -138 +138 @@
         OnlineCalculatorError errorState;
         Add(new Result(TrainingMeanAbsoluteErrorResultName, "Mean of absolute errors of the model on the training partition", new DoubleValue()));
-        double trainingMAE = OnlineMeanAbsoluteErrorCalculator.Calculate(EstimatedTrainingValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes), out errorState);
+        double trainingMAE = OnlineMeanAbsoluteErrorCalculator.Calculate(EstimatedTrainingValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices), out errorState);
         TrainingMeanAbsoluteError = errorState == OnlineCalculatorError.None ? trainingMAE : double.NaN;
       }
@@ -145 +145 @@
         OnlineCalculatorError errorState;
         Add(new Result(TestMeanAbsoluteErrorResultName, "Mean of absolute errors of the model on the test partition", new DoubleValue()));
-        double testMAE = OnlineMeanAbsoluteErrorCalculator.Calculate(EstimatedTestValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndizes), out errorState);
+        double testMAE = OnlineMeanAbsoluteErrorCalculator.Calculate(EstimatedTestValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndices), out errorState);
         TestMeanAbsoluteError = errorState == OnlineCalculatorError.None ? testMAE : double.NaN;
       }
@@ -152 +152 @@
         OnlineCalculatorError errorState;
         Add(new Result(TrainingMeanErrorResultName, "Mean of errors of the model on the training partition", new DoubleValue()));
-        double trainingME = OnlineMeanErrorCalculator.Calculate(EstimatedTrainingValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes), out errorState);
+        double trainingME = OnlineMeanErrorCalculator.Calculate(EstimatedTrainingValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices), out errorState);
         TrainingMeanError = errorState == OnlineCalculatorError.None ? trainingME : double.NaN;
       }
@@ -158 +158 @@
         OnlineCalculatorError errorState;
         Add(new Result(TestMeanErrorResultName, "Mean of errors of the model on the test partition", new DoubleValue()));
-        double testME = OnlineMeanErrorCalculator.Calculate(EstimatedTestValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndizes), out errorState);
+        double testME = OnlineMeanErrorCalculator.Calculate(EstimatedTestValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndices), out errorState);
         TestMeanError = errorState == OnlineCalculatorError.None ? testME : double.NaN;
       }
@@ -166 +166 @@
     protected void CalculateResults() {
       IEnumerable<double> estimatedTrainingValues = EstimatedTrainingValues; // cache values
-      IEnumerable<double> originalTrainingValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes);
+      IEnumerable<double> originalTrainingValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices);
       IEnumerable<double> estimatedTestValues = EstimatedTestValues; // cache values
-      IEnumerable<double> originalTestValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndizes);
+      IEnumerable<double> originalTestValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndices);
 
       OnlineCalculatorError errorState;