Changeset 8139 for trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/kMeans

Timestamp:

06/27/12 17:34:17 (13 years ago)

Author:

mkommend

Message:

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

Location:

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/kMeans

Files:

• KMeansClustering.cs (modified) (1 diff)
• KMeansClusteringSolution.cs (modified) (1 diff)

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/kMeans/KMeansClustering.cs

@@ -85 +85 @@
       Dataset dataset = problemData.Dataset;
       IEnumerable<string> allowedInputVariables = problemData.AllowedInputVariables;
-      IEnumerable<int> rows = problemData.TrainingIndizes;
+      IEnumerable<int> rows = problemData.TrainingIndices;
       int info;
       double[,] centers;

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/kMeans/KMeansClusteringSolution.cs

@@ -52 +52 @@
     public KMeansClusteringSolution(KMeansClusteringModel model, IClusteringProblemData problemData)
       : base(model, problemData) {
-      double trainingIntraClusterSumOfSquares = KMeansClusteringUtil.CalculateIntraClusterSumOfSquares(model, problemData.Dataset, problemData.TrainingIndizes);
-      double testIntraClusterSumOfSquares = KMeansClusteringUtil.CalculateIntraClusterSumOfSquares(model, problemData.Dataset, problemData.TestIndizes);
+      double trainingIntraClusterSumOfSquares = KMeansClusteringUtil.CalculateIntraClusterSumOfSquares(model, problemData.Dataset, problemData.TrainingIndices);
+      double testIntraClusterSumOfSquares = KMeansClusteringUtil.CalculateIntraClusterSumOfSquares(model, problemData.Dataset, problemData.TestIndices);
       this.Add(new Result(TrainingIntraClusterSumOfSquaresResultName, "The sum of squared distances of points of the training partition to the cluster center (is minimized by k-Means).", new DoubleValue(trainingIntraClusterSumOfSquares)));
       this.Add(new Result(TestIntraClusterSumOfSquaresResultName, "The sum of squared distances of points of the test partition to the cluster center (is minimized by k-Means).", new DoubleValue(testIntraClusterSumOfSquares)));