Index: branches/ChangeDatasetOfRegressionModel/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionErrorCharacteristicsCurveView.Designer.cs
===================================================================
--- branches/ChangeDatasetOfRegressionModel/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionErrorCharacteristicsCurveView.Designer.cs	(revision 8032)
+++ branches/ChangeDatasetOfRegressionModel/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionErrorCharacteristicsCurveView.Designer.cs	(revision 8513)
@@ -36,6 +36,6 @@
       // 
       this.chart.Anchor = ((System.Windows.Forms.AnchorStyles)((((System.Windows.Forms.AnchorStyles.Top | System.Windows.Forms.AnchorStyles.Bottom)
-            | System.Windows.Forms.AnchorStyles.Left)
-            | System.Windows.Forms.AnchorStyles.Right)));
+                  | System.Windows.Forms.AnchorStyles.Left)
+                  | System.Windows.Forms.AnchorStyles.Right)));
       chartArea1.Name = "ChartArea1";
       this.chart.ChartAreas.Add(chartArea1);
@@ -73,5 +73,4 @@
       // RegressionSolutionErrorCharacteristicsCurveView
       // 
-      this.AutoScaleDimensions = new System.Drawing.SizeF(6F, 13F);
       this.AutoScaleMode = System.Windows.Forms.AutoScaleMode.Inherit;
       this.Controls.Add(this.label1);
Index: branches/ChangeDatasetOfRegressionModel/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionErrorCharacteristicsCurveView.cs
===================================================================
--- branches/ChangeDatasetOfRegressionModel/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionErrorCharacteristicsCurveView.cs	(revision 8032)
+++ branches/ChangeDatasetOfRegressionModel/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionErrorCharacteristicsCurveView.cs	(revision 8513)
@@ -26,5 +26,4 @@
 using System.Windows.Forms.DataVisualization.Charting;
 using HeuristicLab.MainForm;
-using HeuristicLab.MainForm.WindowsForms;
 
 namespace HeuristicLab.Problems.DataAnalysis.Views {
@@ -32,5 +31,4 @@
   [Content(typeof(IRegressionSolution))]
   public partial class RegressionSolutionErrorCharacteristicsCurveView : DataAnalysisSolutionEvaluationView {
-    private IRegressionSolution constantModel;
     protected const string TrainingSamples = "Training";
     protected const string TestSamples = "Test";
@@ -103,6 +101,6 @@
       if (Content == null) return;
 
+      var constantModel = CreateConstantModel();
       var originalValues = GetOriginalValues().ToList();
-      constantModel = CreateConstantModel();
       var baselineEstimatedValues = GetEstimatedValues(constantModel);
       var baselineResiduals = GetResiduals(originalValues, baselineEstimatedValues);
@@ -117,4 +115,5 @@
       baselineSeries.ToolTip = "Area over Curve: " + CalculateAreaOverCurve(baselineSeries);
       baselineSeries.Tag = constantModel;
+      baselineSeries.LegendToolTip = "Double-click to open model";
       chart.Series.Add(baselineSeries);
 
@@ -131,4 +130,5 @@
       UpdateSeries(estimatedValues, solutionSeries);
       solutionSeries.ToolTip = "Area over Curve: " + CalculateAreaOverCurve(solutionSeries);
+      solutionSeries.LegendToolTip = "Double-click to open model";
       chart.Series.Add(solutionSeries);
     }
@@ -169,8 +169,8 @@
       switch (cmbSamples.SelectedItem.ToString()) {
         case TrainingSamples:
-          originalValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes);
+          originalValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices);
           break;
         case TestSamples:
-          originalValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndizes);
+          originalValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndices);
           break;
         case AllSamples:
@@ -201,9 +201,4 @@
     }
 
-    protected IEnumerable<double> GetbaselineEstimatedValues(IEnumerable<double> originalValues) {
-      double averageTrainingTarget = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes).Average();
-      return Enumerable.Repeat(averageTrainingTarget, originalValues.Count());
-    }
-
     protected virtual List<double> GetResiduals(IEnumerable<double> originalValues, IEnumerable<double> estimatedValues) {
       return originalValues.Zip(estimatedValues, (x, y) => Math.Abs(x - y)).ToList();
@@ -239,5 +234,5 @@
 
     private IRegressionSolution CreateConstantModel() {
-      double averageTrainingTarget = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndizes).Average();
+      double averageTrainingTarget = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices).Average();
       var solution = new ConstantRegressionModel(averageTrainingTarget).CreateRegressionSolution(ProblemData);
       solution.Name = "Baseline";
@@ -248,8 +243,9 @@
     private void chart_MouseMove(object sender, MouseEventArgs e) {
       HitTestResult result = chart.HitTest(e.X, e.Y);
-      if (result.ChartElementType == ChartElementType.LegendItem)
+      if (result.ChartElementType == ChartElementType.LegendItem) {
         Cursor = Cursors.Hand;
-      else
+      } else {
         Cursor = Cursors.Default;
+      }
     }
   }
Index: branches/ChangeDatasetOfRegressionModel/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionEstimatedValuesView.cs
===================================================================
--- branches/ChangeDatasetOfRegressionModel/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionEstimatedValuesView.cs	(revision 8032)
+++ branches/ChangeDatasetOfRegressionModel/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionEstimatedValuesView.cs	(revision 8513)
@@ -93,10 +93,10 @@
           var estimated_test = Content.EstimatedTestValues.GetEnumerator();
 
-          foreach (var row in Content.ProblemData.TrainingIndizes) {
+          foreach (var row in Content.ProblemData.TrainingIndices) {
             estimated_training.MoveNext();
             values[row, 3] = estimated_training.Current.ToString();
           }
 
-          foreach (var row in Content.ProblemData.TestIndizes) {
+          foreach (var row in Content.ProblemData.TestIndices) {
             estimated_test.MoveNext();
             values[row, 4] = estimated_test.Current.ToString();
Index: branches/ChangeDatasetOfRegressionModel/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionLineChartView.cs
===================================================================
--- branches/ChangeDatasetOfRegressionModel/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionLineChartView.cs	(revision 8032)
+++ branches/ChangeDatasetOfRegressionModel/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionLineChartView.cs	(revision 8513)
@@ -72,5 +72,5 @@
         this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].ChartType = SeriesChartType.FastLine;
         this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].EmptyPointStyle.Color = this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Color;
-        this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Points.DataBindXY(Content.ProblemData.TrainingIndizes.ToArray(), Content.EstimatedTrainingValues.ToArray());
+        this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Points.DataBindXY(Content.ProblemData.TrainingIndices.ToArray(), Content.EstimatedTrainingValues.ToArray());
         this.InsertEmptyPoints(this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME]);
         this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Tag = Content;
@@ -79,16 +79,18 @@
         this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].LegendText = ESTIMATEDVALUES_TEST_SERIES_NAME;
         this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].ChartType = SeriesChartType.FastLine;
-        this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].Points.DataBindXY(Content.ProblemData.TestIndizes.ToArray(), Content.EstimatedTestValues.ToArray());
+        this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].Points.DataBindXY(Content.ProblemData.TestIndices.ToArray(), Content.EstimatedTestValues.ToArray());
         this.InsertEmptyPoints(this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME]);
         this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].Tag = Content;
         // series of remaining points
-        int[] allIndizes = Enumerable.Range(0, Content.ProblemData.Dataset.Rows).Except(Content.ProblemData.TrainingIndizes).Except(Content.ProblemData.TestIndizes).ToArray();
+        int[] allIndices = Enumerable.Range(0, Content.ProblemData.Dataset.Rows).Except(Content.ProblemData.TrainingIndices).Except(Content.ProblemData.TestIndices).ToArray();
         var estimatedValues = Content.EstimatedValues.ToArray();
-        List<double> allEstimatedValues = allIndizes.Select(index => estimatedValues[index]).ToList();
+        List<double> allEstimatedValues = allIndices.Select(index => estimatedValues[index]).ToList();
         this.chart.Series.Add(ESTIMATEDVALUES_ALL_SERIES_NAME);
         this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].LegendText = ESTIMATEDVALUES_ALL_SERIES_NAME;
         this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].ChartType = SeriesChartType.FastLine;
-        this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].Points.DataBindXY(allIndizes, allEstimatedValues);
-        this.InsertEmptyPoints(this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME]);
+        if (allEstimatedValues.Count > 0) {
+          this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].Points.DataBindXY(allIndices, allEstimatedValues);
+          this.InsertEmptyPoints(this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME]);
+        }
         this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].Tag = Content;
         this.ToggleSeriesData(this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME]);
@@ -170,8 +172,8 @@
 
       int[] attr = new int[Content.ProblemData.Dataset.Rows + 1]; // add a virtual last row that is again empty to simplify loop further down
-      foreach (var row in Content.ProblemData.TrainingIndizes) {
+      foreach (var row in Content.ProblemData.TrainingIndices) {
         attr[row] += 1;
       }
-      foreach (var row in Content.ProblemData.TestIndizes) {
+      foreach (var row in Content.ProblemData.TestIndices) {
         attr[row] += 2;
       }
@@ -223,23 +225,25 @@
         string targetVariableName = Content.ProblemData.TargetVariable;
 
-        IEnumerable<int> indizes = null;
-        IEnumerable<double> predictedValues = null;
+        IEnumerable<int> indices = null;
+        double[] predictedValues = null;
         switch (series.Name) {
           case ESTIMATEDVALUES_ALL_SERIES_NAME:
-            indizes = Enumerable.Range(0, Content.ProblemData.Dataset.Rows).Except(Content.ProblemData.TrainingIndizes).Except(Content.ProblemData.TestIndizes).ToArray();
+            indices = Enumerable.Range(0, Content.ProblemData.Dataset.Rows).Except(Content.ProblemData.TrainingIndices).Except(Content.ProblemData.TestIndices).ToArray();
             var estimatedValues = Content.EstimatedValues.ToArray();
-            predictedValues = indizes.Select(index => estimatedValues[index]).ToList();
+            predictedValues = indices.Select(index => estimatedValues[index]).ToArray();
             break;
           case ESTIMATEDVALUES_TRAINING_SERIES_NAME:
-            indizes = Content.ProblemData.TrainingIndizes.ToArray();
+            indices = Content.ProblemData.TrainingIndices.ToArray();
             predictedValues = Content.EstimatedTrainingValues.ToArray();
             break;
           case ESTIMATEDVALUES_TEST_SERIES_NAME:
-            indizes = Content.ProblemData.TestIndizes.ToArray();
+            indices = Content.ProblemData.TestIndices.ToArray();
             predictedValues = Content.EstimatedTestValues.ToArray();
             break;
         }
-        series.Points.DataBindXY(indizes, predictedValues);
-        this.InsertEmptyPoints(series);
+        if (predictedValues.Length > 0) {
+          series.Points.DataBindXY(indices, predictedValues);
+          this.InsertEmptyPoints(series);
+        }
         chart.Legends[series.Legend].ForeColor = Color.Black;
         UpdateCursorInterval();
Index: branches/ChangeDatasetOfRegressionModel/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionResidualHistogram.Designer.cs
===================================================================
--- branches/ChangeDatasetOfRegressionModel/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionResidualHistogram.Designer.cs	(revision 8032)
+++ branches/ChangeDatasetOfRegressionModel/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionResidualHistogram.Designer.cs	(revision 8513)
@@ -41,5 +41,5 @@
       this.chart.Location = new System.Drawing.Point(0, 0);
       this.chart.Name = "chart";
-      this.chart.Size = new System.Drawing.Size(358, 225);
+      this.chart.Size = new System.Drawing.Size(289, 220);
       this.chart.TabIndex = 0;
       this.chart.CustomizeLegend += new System.EventHandler<System.Windows.Forms.DataVisualization.Charting.CustomizeLegendEventArgs>(this.chart_CustomizeLegend);
@@ -50,5 +50,4 @@
       // 
       this.AllowDrop = true;
-      this.AutoScaleDimensions = new System.Drawing.SizeF(6F, 13F);
       this.AutoScaleMode = System.Windows.Forms.AutoScaleMode.Inherit;
       this.Controls.Add(this.chart);
Index: branches/ChangeDatasetOfRegressionModel/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionResidualHistogram.cs
===================================================================
--- branches/ChangeDatasetOfRegressionModel/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionResidualHistogram.cs	(revision 8032)
+++ branches/ChangeDatasetOfRegressionModel/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionResidualHistogram.cs	(revision 8513)
@@ -39,16 +39,7 @@
     protected const string TEST_SAMPLES = "Test samples";
     /// <summary>
-    /// used to reduce code duplication
-    /// </summary>
-    protected static string[] ALL_SERIES = new string[] { ALL_SAMPLES, TRAINING_SAMPLES, TEST_SAMPLES };
-    /// <summary>
     /// approximate amount of bins 
     /// </summary>
     protected const double bins = 25;
-    /// <summary>
-    ///  keeps for all series a list for every bin with the position of the bin, the relative frequency of the
-    ///  residuals and the beginning and the end of the interval of the bin
-    ///  </summary>
-    protected Dictionary<string, List<List<double>>> relativeFrequencies;
     #endregion
 
@@ -61,6 +52,5 @@
       : base() {
       InitializeComponent();
-      relativeFrequencies = new Dictionary<string, List<List<double>>>();
-      foreach (string series in ALL_SERIES) {
+      foreach (string series in new List<String>() { ALL_SAMPLES, TRAINING_SAMPLES, TEST_SAMPLES }) {
         chart.Series.Add(series);
         chart.Series[series].LegendText = series;
@@ -71,5 +61,4 @@
         chart.Series[series].BorderColor = Color.Black;
         chart.Series[series].ToolTip = series + " Y = #VALY from #CUSTOMPROPERTY(from) to #CUSTOMPROPERTY(to)";
-        relativeFrequencies[series] = new List<List<double>>();
       }
       //configure axis 
@@ -87,24 +76,22 @@
 
     private void RedrawChart() {
-      foreach (string series in ALL_SERIES) {
-        chart.Series[series].Points.Clear();
-        relativeFrequencies[series].Clear();
+      foreach (Series series in chart.Series) {
+        series.Points.Clear();
       }
       if (Content != null) {
-        Dictionary<string, List<double>> residuals = CalculateResiduals();
-        double realMax = Math.Max(Math.Abs(residuals[ALL_SAMPLES].Min()), Math.Abs(residuals[ALL_SAMPLES].Max()));
-        double roundedMax = HumanRoundMax(realMax);
-        double intervalWidth = (roundedMax * 2.0) / bins;
-        intervalWidth = HumanRoundMax(intervalWidth);
-        // sets roundedMax to a value, so that zero will be in the middle of the x axis
-        double help = realMax / intervalWidth;
-        help = help % 1 < 0.5 ? (int)help : (int)help + 1;
-        roundedMax = help * intervalWidth;
-
-        foreach (string series in ALL_SERIES) {
-          CalculateFrequencies(residuals[series], series, roundedMax, intervalWidth);
-          if (!series.Equals(ALL_SAMPLES))
-            ShowValues(chart.Series[series], relativeFrequencies[series]);
+        List<double> residuals = CalculateResiduals(Content);
+
+        double max = 0.0;
+        foreach (Series series in chart.Series) {
+          CalculateFrequencies(residuals, series);
+          double seriesMax = series.Points.Select(p => p.YValues.First()).Max();
+          max = max < seriesMax ? seriesMax : max;
         }
+
+        // ALL_SAMPLES has to be calculated to know its highest frequency, but it is not shown in the beginning
+        chart.Series.First(s => s.Name.Equals(ALL_SAMPLES)).Points.Clear();
+
+        double roundedMax, intervalWidth;
+        CalculateResidualParameters(residuals, out roundedMax, out intervalWidth);
 
         ChartArea chartArea = chart.ChartAreas[0];
@@ -112,7 +99,5 @@
         chartArea.AxisX.Maximum = roundedMax + intervalWidth;
         // get the highest frequency of a residual of any series
-        chartArea.AxisY.Maximum = (from series in relativeFrequencies.Values
-                                   select (from residual in series
-                                           select residual.ElementAt(1)).Max()).Max();
+        chartArea.AxisY.Maximum = max;
         if (chartArea.AxisY.Maximum < 0.1) {
           chartArea.AxisY.Interval = 0.01;
@@ -132,38 +117,69 @@
     }
 
-    private Dictionary<string, List<double>> CalculateResiduals() {
-      Dictionary<string, List<double>> residuals = new Dictionary<string, List<double>>();
-
-      foreach (string series in ALL_SERIES) {
-        residuals[series] = new List<double>();
-      }
+    private List<double> CalculateResiduals(IRegressionSolution solution) {
+      List<double> residuals = new List<double>();
+
+      IRegressionProblemData problemdata = solution.ProblemData;
+      List<double> targetValues = problemdata.Dataset.GetDoubleValues(Content.ProblemData.TargetVariable).ToList();
+      List<double> estimatedValues = solution.EstimatedValues.ToList();
+
+      for (int i = 0; i < solution.ProblemData.Dataset.Rows; i++) {
+        double residual = estimatedValues[i] - targetValues[i];
+        residuals.Add(residual);
+      }
+      return residuals;
+    }
+
+    private void CalculateFrequencies(List<double> residualValues, Series series) {
+      double roundedMax, intervalWidth;
+      CalculateResidualParameters(residualValues, out roundedMax, out intervalWidth);
+
+      IEnumerable<double> relevantResiduals = residualValues;
       IRegressionProblemData problemdata = Content.ProblemData;
-      List<double> targetValues = problemdata.Dataset.GetDoubleValues(Content.ProblemData.TargetVariable).ToList();
-      List<double> estimatedValues = Content.EstimatedValues.ToList();
-
-      for (int i = 0; i < Content.ProblemData.Dataset.Rows; i++) {
-        double residual = estimatedValues[i] - targetValues[i];
-        residuals[ALL_SAMPLES].Add(residual);
-        if (i >= problemdata.TrainingPartition.Start && i < problemdata.TrainingPartition.End)
-          residuals[TRAINING_SAMPLES].Add(residual);
-        if (i >= problemdata.TestPartition.Start && i < problemdata.TestPartition.End)
-          residuals[TEST_SAMPLES].Add(residual);
-      }
-      return residuals;
-    }
-
-    private void CalculateFrequencies(List<double> residualValues, string series, double max, double intervalWidth) {
+      if (series.Name.Equals(TRAINING_SAMPLES)) {
+        relevantResiduals = residualValues.Skip(problemdata.TrainingPartition.Start).Take(problemdata.TrainingPartition.Size);
+      } else if (series.Name.Equals(TEST_SAMPLES)) {
+        relevantResiduals = residualValues.Skip(problemdata.TestPartition.Start).Take(problemdata.TestPartition.Size);
+      }
+
       double intervalCenter = intervalWidth / 2.0;
-      double sampleCount = residualValues.Count();
-      double current = -max;
+      double sampleCount = relevantResiduals.Count();
+      double current = -roundedMax;
+      DataPointCollection seriesPoints = series.Points;
 
       for (int i = 0; i <= bins; i++) {
-        IEnumerable<double> help = residualValues.Where(x => x >= (current - intervalCenter) && x < (current + intervalCenter));
-        relativeFrequencies[series].Add(new List<double>() { current, help.Count() / sampleCount, current - intervalCenter, current + intervalCenter });
+        IEnumerable<double> help = relevantResiduals.Where(x => x >= (current - intervalCenter) && x < (current + intervalCenter));
+        seriesPoints.AddXY(current, help.Count() / sampleCount);
+        seriesPoints[seriesPoints.Count - 1]["from"] = (current - intervalCenter).ToString();
+        seriesPoints[seriesPoints.Count - 1]["to"] = (current + intervalCenter).ToString();
         current += intervalWidth;
       }
     }
 
-    private double HumanRoundMax(double max) {
+    private void ToggleSeriesData(Series series) {
+      if (series.Points.Count > 0) {  //checks if series is shown
+        if (chart.Series.Any(s => s != series && s.Points.Count > 0)) {
+          series.Points.Clear();
+        }
+      } else if (Content != null) {
+        List<double> residuals = CalculateResiduals(Content);
+        CalculateFrequencies(residuals, series);
+        chart.Legends[series.Legend].ForeColor = Color.Black;
+        chart.Refresh();
+      }
+    }
+
+    private static void CalculateResidualParameters(List<double> residuals, out double roundedMax, out double intervalWidth) {
+      double realMax = Math.Max(Math.Abs(residuals.Min()), Math.Abs(residuals.Max()));
+      roundedMax = HumanRoundMax(realMax);
+      intervalWidth = (roundedMax * 2.0) / bins;
+      intervalWidth = HumanRoundMax(intervalWidth);
+      // sets roundedMax to a value, so that zero will be in the middle of the x axis
+      double help = realMax / intervalWidth;
+      help = help % 1 < 0.5 ? (int)help : (int)help + 1;
+      roundedMax = help * intervalWidth;
+    }
+
+    private static double HumanRoundMax(double max) {
       double base10;
       if (max > 0) base10 = Math.Pow(10.0, Math.Floor(Math.Log10(max)));
@@ -216,25 +232,4 @@
     }
     #endregion
-
-    private void ToggleSeriesData(Series series) {
-      if (series.Points.Count > 0) {  //checks if series is shown
-        if (chart.Series.Any(s => s != series && s.Points.Count > 0)) {
-          series.Points.Clear();
-        }
-      } else if (Content != null) {
-        ShowValues(series, relativeFrequencies[series.Name]);
-        chart.Legends[series.Legend].ForeColor = Color.Black;
-        chart.Refresh();
-      }
-    }
-    private void ShowValues(Series series, List<List<double>> relativeSeriesFrequencies) {
-      DataPointCollection seriesPoints = series.Points;
-
-      foreach (var valueList in relativeSeriesFrequencies) {
-        seriesPoints.AddXY(valueList[0], valueList[1]);
-        seriesPoints[seriesPoints.Count - 1]["from"] = valueList[2].ToString();
-        seriesPoints[seriesPoints.Count - 1]["to"] = valueList[3].ToString();
-      }
-    }
   }
 }
Index: branches/ChangeDatasetOfRegressionModel/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionScatterPlotView.cs
===================================================================
--- branches/ChangeDatasetOfRegressionModel/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionScatterPlotView.cs	(revision 8032)
+++ branches/ChangeDatasetOfRegressionModel/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionScatterPlotView.cs	(revision 8513)
@@ -148,8 +148,8 @@
         if (this.chart.Series[TRAINING_SERIES].Points.Count > 0)
           this.chart.Series[TRAINING_SERIES].Points.DataBindXY(Content.EstimatedTrainingValues.ToArray(), "",
-            dataset.GetDoubleValues(targetVariableName, Content.ProblemData.TrainingIndizes).ToArray(), "");
+            dataset.GetDoubleValues(targetVariableName, Content.ProblemData.TrainingIndices).ToArray(), "");
         if (this.chart.Series[TEST_SERIES].Points.Count > 0)
           this.chart.Series[TEST_SERIES].Points.DataBindXY(Content.EstimatedTestValues.ToArray(), "",
-           dataset.GetDoubleValues(targetVariableName, Content.ProblemData.TestIndizes).ToArray(), "");
+           dataset.GetDoubleValues(targetVariableName, Content.ProblemData.TestIndices).ToArray(), "");
 
         double max = Content.EstimatedTrainingValues.Concat(Content.EstimatedTestValues.Concat(Content.EstimatedValues.Concat(dataset.GetDoubleValues(targetVariableName)))).Max();
@@ -196,9 +196,9 @@
           case TRAINING_SERIES:
             predictedValues = Content.EstimatedTrainingValues.ToArray();
-            targetValues = Content.ProblemData.Dataset.GetDoubleValues(targetVariableName, Content.ProblemData.TrainingIndizes).ToArray();
+            targetValues = Content.ProblemData.Dataset.GetDoubleValues(targetVariableName, Content.ProblemData.TrainingIndices).ToArray();
             break;
           case TEST_SERIES:
             predictedValues = Content.EstimatedTestValues.ToArray();
-            targetValues = Content.ProblemData.Dataset.GetDoubleValues(targetVariableName, Content.ProblemData.TestIndizes).ToArray();
+            targetValues = Content.ProblemData.Dataset.GetDoubleValues(targetVariableName, Content.ProblemData.TestIndices).ToArray();
             break;
         }
