Index: /branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/ClassificationEnsembleModel.cs
===================================================================
--- /branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/ClassificationEnsembleModel.cs	(revision 5662)
+++ /branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/ClassificationEnsembleModel.cs	(revision 5662)
@@ -0,0 +1,94 @@
+#region License Information
+/* HeuristicLab
+ * Copyright (C) 2002-2011 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.Collections.Generic;
+using System.Linq;
+using HeuristicLab.Common;
+using HeuristicLab.Core;
+using HeuristicLab.Data;
+using HeuristicLab.Operators;
+using HeuristicLab.Parameters;
+using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HeuristicLab.Optimization;
+using System;
+
+namespace HeuristicLab.Problems.DataAnalysis {
+  /// <summary>
+  /// Represents classification solutions that contain an ensemble of multiple classification models
+  /// </summary>
+  [StorableClass]
+  [Item("ClassificationEnsembleModel", "A classification model that contains an ensemble of multiple classification models")]
+  public class ClassificationEnsembleModel : NamedItem, IClassificationEnsembleModel {
+
+    [Storable]
+    private List<IClassificationModel> models;
+    public IEnumerable<IClassificationModel> Models {
+      get { return new List<IClassificationModel>(models); }
+    }
+    [StorableConstructor]
+    protected ClassificationEnsembleModel(bool deserializing) : base(deserializing) { }
+    protected ClassificationEnsembleModel(ClassificationEnsembleModel original, Cloner cloner)
+      : base(original, cloner) {
+      this.models = original.Models.Select(m => cloner.Clone(m)).ToList();
+    }
+    public ClassificationEnsembleModel(IEnumerable<IClassificationModel> models)
+      : base() {
+      this.name = ItemName;
+      this.description = ItemDescription;
+      this.models = new List<IClassificationModel>(models);
+    }
+
+    public override IDeepCloneable Clone(Cloner cloner) {
+      return new ClassificationEnsembleModel(this, cloner);
+    }
+
+    #region IClassificationEnsembleModel Members
+
+    public IEnumerable<IEnumerable<double>> GetEstimatedClassValueVectors(Dataset dataset, IEnumerable<int> rows) {
+      var estimatedValuesEnumerators = (from model in models
+                                        select model.GetEstimatedClassValues(dataset, rows).GetEnumerator())
+                                       .ToList();
+
+      while (estimatedValuesEnumerators.All(en => en.MoveNext())) {
+        yield return from enumerator in estimatedValuesEnumerators
+                     select enumerator.Current;
+      }
+    }
+
+    #endregion
+
+    #region IClassificationModel Members
+
+    public IEnumerable<double> GetEstimatedClassValues(Dataset dataset, IEnumerable<int> rows) {
+      foreach (var estimatedValuesVector in GetEstimatedClassValueVectors(dataset, rows)) {
+        // return the class which is most often occuring
+        yield return
+          estimatedValuesVector
+          .GroupBy(x => x)
+          .OrderBy(g => -g.Count())
+          .Select(g => g.Key)
+          .First();
+      }
+    }
+
+    #endregion
+  }
+}
Index: /branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/HeuristicLab.Problems.DataAnalysis-3.4.csproj
===================================================================
--- /branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/HeuristicLab.Problems.DataAnalysis-3.4.csproj	(revision 5661)
+++ /branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/HeuristicLab.Problems.DataAnalysis-3.4.csproj	(revision 5662)
@@ -114,4 +114,8 @@
     <Compile Include="ClusteringProblemData.cs" />
     <Compile Include="ClusteringSolution.cs" />
+    <Compile Include="ClassificationEnsembleModel.cs" />
+    <Compile Include="Interfaces\Classification\IClassificationEnsembleModel.cs" />
+    <Compile Include="Interfaces\Regression\IRegressionEnsembleModel.cs" />
+    <Compile Include="RegressionEnsembleModel.cs" />
     <Compile Include="DiscriminantFunctionClassificationModel.cs" />
     <Compile Include="DiscriminantFunctionClassificationSolution.cs" />
Index: /branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/Classification/IClassificationEnsembleModel.cs
===================================================================
--- /branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/Classification/IClassificationEnsembleModel.cs	(revision 5662)
+++ /branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/Classification/IClassificationEnsembleModel.cs	(revision 5662)
@@ -0,0 +1,28 @@
+﻿#region License Information
+/* HeuristicLab
+ * Copyright (C) 2002-2011 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.Collections.Generic;
+namespace HeuristicLab.Problems.DataAnalysis {
+  public interface IClassificationEnsembleModel : IClassificationModel {
+    IEnumerable<IClassificationModel> Models { get; }
+    IEnumerable<IEnumerable<double>> GetEstimatedClassValueVectors(Dataset dataset, IEnumerable<int> rows);
+  }
+}
Index: /branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/Regression/IRegressionEnsembleModel.cs
===================================================================
--- /branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/Regression/IRegressionEnsembleModel.cs	(revision 5662)
+++ /branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/Regression/IRegressionEnsembleModel.cs	(revision 5662)
@@ -0,0 +1,28 @@
+﻿#region License Information
+/* HeuristicLab
+ * Copyright (C) 2002-2011 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.Collections.Generic;
+namespace HeuristicLab.Problems.DataAnalysis {
+  public interface IRegressionEnsembleModel : IRegressionModel {
+    IEnumerable<IRegressionModel> Models { get; }
+    IEnumerable<IEnumerable<double>> GetEstimatedValueVectors(Dataset dataset, IEnumerable<int> rows);
+  }
+}
Index: /branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/RegressionEnsembleModel.cs
===================================================================
--- /branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/RegressionEnsembleModel.cs	(revision 5662)
+++ /branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/RegressionEnsembleModel.cs	(revision 5662)
@@ -0,0 +1,88 @@
+#region License Information
+/* HeuristicLab
+ * Copyright (C) 2002-2011 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.Collections.Generic;
+using System.Linq;
+using HeuristicLab.Common;
+using HeuristicLab.Core;
+using HeuristicLab.Data;
+using HeuristicLab.Operators;
+using HeuristicLab.Parameters;
+using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HeuristicLab.Optimization;
+using System;
+
+namespace HeuristicLab.Problems.DataAnalysis {
+  /// <summary>
+  /// Represents regression solutions that contain an ensemble of multiple regression models
+  /// </summary>
+  [StorableClass]
+  [Item("RegressionEnsembleModel", "A regression model that contains an ensemble of multiple regression models")]
+  public class RegressionEnsembleModel : NamedItem, IRegressionEnsembleModel {
+
+    [Storable]
+    private List<IRegressionModel> models;
+    public IEnumerable<IRegressionModel> Models {
+      get { return new List<IRegressionModel>(models); }
+    }
+    [StorableConstructor]
+    protected RegressionEnsembleModel(bool deserializing) : base(deserializing) { }
+    protected RegressionEnsembleModel(RegressionEnsembleModel original, Cloner cloner)
+      : base(original, cloner) {
+      this.models = original.Models.Select(m => cloner.Clone(m)).ToList();
+    }
+    public RegressionEnsembleModel(IEnumerable<IRegressionModel> models)
+      : base() {
+      this.name = ItemName;
+      this.description = ItemDescription;
+      this.models = new List<IRegressionModel>(models);
+    }
+
+    public override IDeepCloneable Clone(Cloner cloner) {
+      return new RegressionEnsembleModel(this, cloner);
+    }
+
+    #region IRegressionEnsembleModel Members
+
+    public IEnumerable<IEnumerable<double>> GetEstimatedValueVectors(Dataset dataset, IEnumerable<int> rows) {
+      var estimatedValuesEnumerators = (from model in models
+                                        select model.GetEstimatedValues(dataset, rows).GetEnumerator())
+                                       .ToList();
+
+      while (estimatedValuesEnumerators.All(en => en.MoveNext())) {
+        yield return from enumerator in estimatedValuesEnumerators
+                     select enumerator.Current;
+      }
+    }
+
+    #endregion
+
+    #region IRegressionModel Members
+
+    public IEnumerable<double> GetEstimatedValues(Dataset dataset, IEnumerable<int> rows) {
+      foreach (var estimatedValuesVector in GetEstimatedValueVectors(dataset, rows)) {
+        yield return estimatedValuesVector.Average();
+      }
+    }
+
+    #endregion
+  }
+}
