Index: stable/HeuristicLab.Algorithms.DataAnalysis.Views/3.4/GaussianProcessRegressionSolutionEstimatedValuesView.Designer.cs
===================================================================
--- stable/HeuristicLab.Algorithms.DataAnalysis.Views/3.4/GaussianProcessRegressionSolutionEstimatedValuesView.Designer.cs	(revision 13951)
+++ stable/HeuristicLab.Algorithms.DataAnalysis.Views/3.4/GaussianProcessRegressionSolutionEstimatedValuesView.Designer.cs	(revision 13951)
@@ -0,0 +1,62 @@
+﻿#region License Information
+/* HeuristicLab
+ * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ *
+ * This file is part of HeuristicLab.
+ *
+ * HeuristicLab is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * HeuristicLab is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
+ */
+#endregion
+namespace HeuristicLab.Algorithms.DataAnalysis.Views {
+  partial class GaussianProcessRegressionSolutionEstimatedValuesView {
+    /// <summary> 
+    /// Required designer variable.
+    /// </summary>
+    private System.ComponentModel.IContainer components = null;
+
+    /// <summary> 
+    /// Clean up any resources being used.
+    /// </summary>
+    /// <param name="disposing">true if managed resources should be disposed; otherwise, false.</param>
+    protected override void Dispose(bool disposing) {
+      if (disposing && (components != null)) {
+        components.Dispose();
+      }
+      base.Dispose(disposing);
+    }
+
+    #region Component Designer generated code
+
+    /// <summary> 
+    /// Required method for Designer support - do not modify 
+    /// the contents of this method with the code editor.
+    /// </summary>
+    private void InitializeComponent() {
+      this.SuspendLayout();
+      // 
+      // EstimatedValuesView
+      // 
+      this.AllowDrop = true;
+      this.AutoScaleDimensions = new System.Drawing.SizeF(6F, 13F);
+      this.AutoScaleMode = System.Windows.Forms.AutoScaleMode.Inherit;
+      this.Name = "EstimatedValuesView";
+      this.Size = new System.Drawing.Size(310, 285);
+      this.ResumeLayout(false);
+
+    }
+
+    #endregion
+
+  }
+}
Index: stable/HeuristicLab.Algorithms.DataAnalysis.Views/3.4/GaussianProcessRegressionSolutionEstimatedValuesView.cs
===================================================================
--- stable/HeuristicLab.Algorithms.DataAnalysis.Views/3.4/GaussianProcessRegressionSolutionEstimatedValuesView.cs	(revision 13951)
+++ stable/HeuristicLab.Algorithms.DataAnalysis.Views/3.4/GaussianProcessRegressionSolutionEstimatedValuesView.cs	(revision 13951)
@@ -0,0 +1,72 @@
+﻿#region License Information
+/* HeuristicLab
+ * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ *
+ * This file is part of HeuristicLab.
+ *
+ * HeuristicLab is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * HeuristicLab is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
+ */
+#endregion
+using System.Linq;
+using System.Windows.Forms;
+using HeuristicLab.Data;
+using HeuristicLab.MainForm;
+using HeuristicLab.Problems.DataAnalysis.Views;
+
+namespace HeuristicLab.Algorithms.DataAnalysis.Views {
+  [View("Estimated Values")]
+  [Content(typeof(GaussianProcessRegressionSolution), false)]
+  public partial class GaussianProcessRegressionSolutionEstimatedValuesView : RegressionSolutionEstimatedValuesView {
+    private const string ESTIMATEDVARIANCE_TRAINING_SERIES_NAME = "Estimated Variance (training)";
+    private const string ESTIMATEDVARIANCE_TEST_SERIES_NAME = "Estimated Variance (test)";
+
+    public new GaussianProcessRegressionSolution Content {
+      get { return (GaussianProcessRegressionSolution)base.Content; }
+      set { base.Content = value; }
+    }
+
+    public GaussianProcessRegressionSolutionEstimatedValuesView()
+      : base() {
+      InitializeComponent();
+    }
+
+
+    protected override StringMatrix CreateValueMatrix() {
+      var matrix = base.CreateValueMatrix();
+
+      var columnNames = matrix.ColumnNames.Concat(new[] { ESTIMATEDVARIANCE_TRAINING_SERIES_NAME, ESTIMATEDVARIANCE_TEST_SERIES_NAME }).ToList();
+      ((IStringConvertibleMatrix)matrix).Columns += 2;
+      matrix.ColumnNames = columnNames;
+
+      var trainingRows = Content.ProblemData.TrainingIndices;
+      var testRows = Content.ProblemData.TestIndices;
+
+      var estimated_var_training = Content.GetEstimatedVariance(trainingRows).GetEnumerator();
+      var estimated_var_test = Content.GetEstimatedVariance(testRows).GetEnumerator();
+
+      foreach (var row in Content.ProblemData.TrainingIndices) {
+        estimated_var_training.MoveNext();
+        matrix[row, 7] = estimated_var_training.Current.ToString();
+      }
+
+      foreach (var row in Content.ProblemData.TestIndices) {
+        estimated_var_test.MoveNext();
+        matrix[row, 8] = estimated_var_test.Current.ToString();
+      }
+
+
+      return matrix;
+    }
+  }
+}
Index: stable/HeuristicLab.Algorithms.DataAnalysis.Views/3.4/HeuristicLab.Algorithms.DataAnalysis.Views-3.4.csproj
===================================================================
--- stable/HeuristicLab.Algorithms.DataAnalysis.Views/3.4/HeuristicLab.Algorithms.DataAnalysis.Views-3.4.csproj	(revision 13950)
+++ stable/HeuristicLab.Algorithms.DataAnalysis.Views/3.4/HeuristicLab.Algorithms.DataAnalysis.Views-3.4.csproj	(revision 13951)
@@ -125,4 +125,10 @@
   </ItemGroup>
   <ItemGroup>
+    <Compile Include="GaussianProcessRegressionSolutionEstimatedValuesView.cs">
+      <SubType>UserControl</SubType>
+    </Compile>
+    <Compile Include="GaussianProcessRegressionSolutionEstimatedValuesView.Designer.cs">
+      <DependentUpon>GaussianProcessRegressionSolutionEstimatedValuesView.cs</DependentUpon>
+    </Compile>
     <Compile Include="MeanProdView.cs">
       <SubType>UserControl</SubType>
Index: stable/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionEstimatedValuesView.cs
===================================================================
--- stable/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionEstimatedValuesView.cs	(revision 13950)
+++ stable/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionEstimatedValuesView.cs	(revision 13951)
@@ -25,5 +25,4 @@
 using HeuristicLab.Data.Views;
 using HeuristicLab.MainForm;
-using HeuristicLab.MainForm.WindowsForms;
 
 namespace HeuristicLab.Problems.DataAnalysis.Views {
@@ -68,9 +67,9 @@
     }
 
-    private void Content_ProblemDataChanged(object sender, EventArgs e) {
+    protected virtual void Content_ProblemDataChanged(object sender, EventArgs e) {
       OnContentChanged();
     }
 
-    private void Content_ModelChanged(object sender, EventArgs e) {
+    protected virtual void Content_ModelChanged(object sender, EventArgs e) {
       OnContentChanged();
     }
@@ -81,40 +80,45 @@
     }
 
-    private void UpdateEstimatedValues() {
+    protected virtual StringMatrix CreateValueMatrix() {
+      string[,] values = new string[Content.ProblemData.Dataset.Rows, 7];
+
+      double[] target = Content.ProblemData.Dataset.GetDoubleValues(Content.ProblemData.TargetVariable).ToArray();
+      var estimated = Content.EstimatedValues.GetEnumerator();
+      var estimated_training = Content.EstimatedTrainingValues.GetEnumerator();
+      var estimated_test = Content.EstimatedTestValues.GetEnumerator();
+
+      foreach (var row in Content.ProblemData.TrainingIndices) {
+        estimated_training.MoveNext();
+        values[row, 3] = estimated_training.Current.ToString();
+      }
+
+      foreach (var row in Content.ProblemData.TestIndices) {
+        estimated_test.MoveNext();
+        values[row, 4] = estimated_test.Current.ToString();
+      }
+
+      foreach (var row in Enumerable.Range(0, Content.ProblemData.Dataset.Rows)) {
+        estimated.MoveNext();
+        double est = estimated.Current;
+        double res = Math.Abs(est - target[row]);
+        values[row, 0] = row.ToString();
+        values[row, 1] = target[row].ToString();
+        values[row, 2] = est.ToString();
+        values[row, 5] = Math.Abs(res).ToString();
+        values[row, 6] = Math.Abs(res / target[row]).ToString();
+      }
+
+      var matrix = new StringMatrix(values);
+      matrix.ColumnNames = new string[] { "Id", TARGETVARIABLE_SERIES_NAME, ESTIMATEDVALUES_SERIES_NAME, ESTIMATEDVALUES_TRAINING_SERIES_NAME, ESTIMATEDVALUES_TEST_SERIES_NAME, "Absolute Error (all)", "Relative Error (all)" };
+      matrix.SortableView = true;
+      return matrix;
+    }
+
+    protected virtual void UpdateEstimatedValues() {
       if (InvokeRequired) Invoke((Action)UpdateEstimatedValues);
       else {
         StringMatrix matrix = null;
         if (Content != null) {
-          string[,] values = new string[Content.ProblemData.Dataset.Rows, 7];
-
-          double[] target = Content.ProblemData.Dataset.GetDoubleValues(Content.ProblemData.TargetVariable).ToArray();
-          var estimated = Content.EstimatedValues.GetEnumerator();
-          var estimated_training = Content.EstimatedTrainingValues.GetEnumerator();
-          var estimated_test = Content.EstimatedTestValues.GetEnumerator();
-
-          foreach (var row in Content.ProblemData.TrainingIndices) {
-            estimated_training.MoveNext();
-            values[row, 3] = estimated_training.Current.ToString();
-          }
-
-          foreach (var row in Content.ProblemData.TestIndices) {
-            estimated_test.MoveNext();
-            values[row, 4] = estimated_test.Current.ToString();
-          }
-
-          foreach (var row in Enumerable.Range(0, Content.ProblemData.Dataset.Rows)) {
-            estimated.MoveNext();
-            double est = estimated.Current;
-            double res = Math.Abs(est - target[row]);
-            values[row, 0] = row.ToString();
-            values[row, 1] = target[row].ToString();
-            values[row, 2] = est.ToString();
-            values[row, 5] = Math.Abs(res).ToString();
-            values[row, 6] = Math.Abs(res / target[row]).ToString();
-          }
-
-          matrix = new StringMatrix(values);
-          matrix.ColumnNames = new string[] { "Id", TARGETVARIABLE_SERIES_NAME, ESTIMATEDVALUES_SERIES_NAME, ESTIMATEDVALUES_TRAINING_SERIES_NAME, ESTIMATEDVALUES_TEST_SERIES_NAME, "Absolute Error (all)", "Relative Error (all)" };
-          matrix.SortableView = true;
+          matrix = CreateValueMatrix();
         }
         matrixView.Content = matrix;
