Changeset 7531 for branches/ClassificationEnsembleVoting/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/WeightCalculators/NeighbourhoodWeightCalculator.cs

Timestamp:

02/27/12 16:11:34 (12 years ago)

Author:

sforsten

Message:

#1776:

• 2 more strategies have been implemented
• major changes in the inheritance have been made to make it possible to add strategies which don't use a voting strategy with weights
• ClassificationEnsembleSolutionEstimatedClassValuesView doesn't currently show the confidence (has been removed for test purpose)

File:

• branches/ClassificationEnsembleVoting/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/WeightCalculators/NeighbourhoodWeightCalculator.cs (modified) (3 diffs)

branches/ClassificationEnsembleVoting/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/WeightCalculators/NeighbourhoodWeightCalculator.cs

@@ -33 +33 @@
   [StorableClass]
   [Item("NeighbourhoodWeightCalculator", "")]
-  public class NeighbourhoodWeightCalculator : WeightCalculator {
+  public class NeighbourhoodWeightCalculator : DiscriminantClassificationWeightCalculator {
 
     public NeighbourhoodWeightCalculator()
@@ -49 +49 @@
     }
 
-    protected override IEnumerable<double> CalculateWeights(ItemCollection<IClassificationSolution> classificationSolutions) {
-      if (classificationSolutions.Count <= 0)
-        return new List<double>();
-
-      if (!classificationSolutions.All(x => x is IDiscriminantFunctionClassificationSolution))
-        return Enumerable.Repeat<double>(1, classificationSolutions.Count);
-
+    protected override IEnumerable<double> DiscriminantCalculateWeights(ItemCollection<IDiscriminantFunctionClassificationSolution> discriminantSolutions) {
       List<List<double>> estimatedTrainingValEnumerators = new List<List<double>>();
       List<List<double>> estimatedTrainingClassValEnumerators = new List<List<double>>();
-      IDiscriminantFunctionClassificationSolution discriminantSolution;
-      foreach (var solution in classificationSolutions) {
-        discriminantSolution = (IDiscriminantFunctionClassificationSolution)solution;
-        estimatedTrainingValEnumerators.Add(discriminantSolution.EstimatedTrainingValues.ToList());
-        estimatedTrainingClassValEnumerators.Add(discriminantSolution.EstimatedTrainingClassValues.ToList());
+      foreach (var solution in discriminantSolutions) {
+        estimatedTrainingValEnumerators.Add(solution.EstimatedTrainingValues.ToList());
+        estimatedTrainingClassValEnumerators.Add(solution.EstimatedTrainingClassValues.ToList());
       }
 
-      List<double> weights = Enumerable.Repeat<double>(0, classificationSolutions.Count()).ToList<double>();
+      List<double> weights = Enumerable.Repeat<double>(0, discriminantSolutions.Count()).ToList<double>();
 
-      IClassificationProblemData problemData = classificationSolutions.ElementAt(0).ProblemData;
+      IClassificationProblemData problemData = discriminantSolutions.ElementAt(0).ProblemData;
       List<double> targetValues = problemData.Dataset.GetDoubleValues(problemData.TargetVariable).ToList();
       List<double> trainingVal = GetValues(targetValues, problemData.TrainingIndizes).ToList();
@@ -93 +85 @@
       return weights;
     }
-
-    private IEnumerable<double> GetValues(IList<double> targetValues, IEnumerable<int> indizes) {
-      return from i in indizes
-             select targetValues[i];
-    }
   }
 }