Changeset 8206 for branches/GP-MoveOperators/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear

Timestamp:

07/03/12 16:46:35 (12 years ago)

Author:

gkronber

Message:

#1847: merged r8084:8205 from trunk into GP move operators branch

Location:

branches/GP-MoveOperators

Files:

• . (modified) (1 prop)
• HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/LinearDiscriminantAnalysis.cs (modified) (1 diff)
• HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/LinearRegression.cs (modified) (1 diff)
• HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/MultinomialLogitClassification.cs (modified) (2 diffs)

branches/GP-MoveOperators/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/LinearDiscriminantAnalysis.cs

@@ -68 +68 @@
       string targetVariable = problemData.TargetVariable;
       IEnumerable<string> allowedInputVariables = problemData.AllowedInputVariables;
-      IEnumerable<int> rows = problemData.TrainingIndizes;
+      IEnumerable<int> rows = problemData.TrainingIndices;
       int nClasses = problemData.ClassNames.Count();
       double[,] inputMatrix = AlglibUtil.PrepareInputMatrix(dataset, allowedInputVariables.Concat(new string[] { targetVariable }), rows);

branches/GP-MoveOperators/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/LinearRegression.cs

@@ -72 +72 @@
       string targetVariable = problemData.TargetVariable;
       IEnumerable<string> allowedInputVariables = problemData.AllowedInputVariables;
-      IEnumerable<int> rows = problemData.TrainingIndizes;
+      IEnumerable<int> rows = problemData.TrainingIndices;
       double[,] inputMatrix = AlglibUtil.PrepareInputMatrix(dataset, allowedInputVariables.Concat(new string[] { targetVariable }), rows);
       if (inputMatrix.Cast<double>().Any(x => double.IsNaN(x) || double.IsInfinity(x)))

branches/GP-MoveOperators/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/MultinomialLogitClassification.cs

@@ -69 +69 @@
       string targetVariable = problemData.TargetVariable;
       IEnumerable<string> allowedInputVariables = problemData.AllowedInputVariables;
-      IEnumerable<int> rows = problemData.TrainingIndizes;
+      IEnumerable<int> rows = problemData.TrainingIndices;
       double[,] inputMatrix = AlglibUtil.PrepareInputMatrix(dataset, allowedInputVariables.Concat(new string[] { targetVariable }), rows);
       if (inputMatrix.Cast<double>().Any(x => double.IsNaN(x) || double.IsInfinity(x)))
@@ -81 +81 @@
       int nClasses = classValues.Count();
       // map original class values to values [0..nClasses-1]
-      Dictionary<double, double> classIndizes = new Dictionary<double, double>();
+      Dictionary<double, double> classIndices = new Dictionary<double, double>();
       for (int i = 0; i < nClasses; i++) {
-        classIndizes[classValues[i]] = i;
+        classIndices[classValues[i]] = i;
       }
       for (int row = 0; row < nRows; row++) {
-        inputMatrix[row, nFeatures] = classIndizes[inputMatrix[row, nFeatures]];
+        inputMatrix[row, nFeatures] = classIndices[inputMatrix[row, nFeatures]];
       }
       int info;