Changeset 17054

Timestamp:

07/04/19 13:00:24 (4 years ago)

Author:

mkommend

Message:

#2955: Merged r16241, r16243, r16244, r16763 into stable.

Location:

stable

Files:

• . (modified) (1 prop)
• HeuristicLab.Algorithms.DataAnalysis (modified) (1 prop)
• HeuristicLab.Algorithms.DataAnalysis/3.4 (modified) (1 prop)
• HeuristicLab.Algorithms.DataAnalysis/3.4/NearestNeighbour/NearestNeighbourModel.cs (modified) (1 diff)
• HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkEnsembleModel.cs (modified) (1 diff)
• HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkModel.cs (modified) (1 diff)
• HeuristicLab.Algorithms.DataAnalysis/3.4/RandomForest/RandomForestModel.cs (modified) (1 diff)
• HeuristicLab.Algorithms.DataAnalysis/3.4/SupportVectorMachine/SupportVectorMachineModel.cs (modified) (2 diffs)
• HeuristicLab.Algorithms.DataAnalysis/3.4/kMeans/KMeansClusteringModel.cs (modified) (3 diffs)
• HeuristicLab.Problems.DataAnalysis (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Classification (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationModel.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4 (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SymbolicRegressionModel.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/SymbolicDataAnalysisModel.cs (modified) (2 diffs)
• HeuristicLab.Problems.DataAnalysis.Trading/3.4/ProblemData.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Trading/3.4/Symbolic/Model.cs (modified) (2 diffs)
• HeuristicLab.Problems.DataAnalysis.Views (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Views/3.4 (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Views/3.4/Solution Views/DataAnalysisSolutionView.cs (modified) (2 diffs)
• HeuristicLab.Problems.DataAnalysis/3.4 (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis/3.4/Dataset.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ClassificationModel.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ClassificationProblemData.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ClassificationSolutionBase.cs (modified) (2 diffs)
• HeuristicLab.Problems.DataAnalysis/3.4/Implementation/ConstantModel.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis/3.4/Implementation/DataAnalysisModel.cs (modified) (2 diffs)
• HeuristicLab.Problems.DataAnalysis/3.4/Implementation/DataAnalysisProblemData.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis/3.4/Implementation/DataAnalysisSolution.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Regression/RegressionModel.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Regression/RegressionProblemData.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Regression/RegressionSolutionBase.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis/3.4/Implementation/TimeSeriesPrognosis/TimeSeriesPrognosisProblemData.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/Classification/IClassificationModel.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/IDataAnalysisModel.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/IDataAnalysisProblemData.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/IDataset.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/Regression/IRegressionModel.cs (modified) (1 diff)

stable/HeuristicLab.Algorithms.DataAnalysis/3.4/NearestNeighbour/NearestNeighbourModel.cs

@@ -262 +262 @@
 
 
+    public bool IsProblemDataCompatible(IRegressionProblemData problemData, out string errorMessage) {
+      return RegressionModel.IsProblemDataCompatible(this, problemData, out errorMessage);
+    }
+
+    public override bool IsProblemDataCompatible(IDataAnalysisProblemData problemData, out string errorMessage) {
+      if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null.");
+
+      var regressionProblemData = problemData as IRegressionProblemData;
+      if (regressionProblemData != null)
+        return IsProblemDataCompatible(regressionProblemData, out errorMessage);
+
+      var classificationProblemData = problemData as IClassificationProblemData;
+      if (classificationProblemData != null)
+        return IsProblemDataCompatible(classificationProblemData, out errorMessage);
+
+      throw new ArgumentException("The problem data is not compatible with this nearest neighbour model. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
+    }
+
     IRegressionSolution IRegressionModel.CreateRegressionSolution(IRegressionProblemData problemData) {
       return new NearestNeighbourRegressionSolution(this, new RegressionProblemData(problemData));

stable/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkEnsembleModel.cs

@@ -130 +130 @@
     }
 
+
+    public bool IsProblemDataCompatible(IRegressionProblemData problemData, out string errorMessage) {
+      return RegressionModel.IsProblemDataCompatible(this, problemData, out errorMessage);
+    }
+
+    public override bool IsProblemDataCompatible(IDataAnalysisProblemData problemData, out string errorMessage) {
+      if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null.");
+
+      var regressionProblemData = problemData as IRegressionProblemData;
+      if (regressionProblemData != null)
+        return IsProblemDataCompatible(regressionProblemData, out errorMessage);
+
+      var classificationProblemData = problemData as IClassificationProblemData;
+      if (classificationProblemData != null)
+        return IsProblemDataCompatible(classificationProblemData, out errorMessage);
+
+      throw new ArgumentException("The problem data is not compatible with this neural network ensemble. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
+    }
+
     public IRegressionSolution CreateRegressionSolution(IRegressionProblemData problemData) {
       return new NeuralNetworkEnsembleRegressionSolution(this, new RegressionEnsembleProblemData(problemData));

stable/HeuristicLab.Algorithms.DataAnalysis/3.4/NeuralNetwork/NeuralNetworkModel.cs

@@ -134 +134 @@
     }
 
+    public bool IsProblemDataCompatible(IRegressionProblemData problemData, out string errorMessage) {
+      return RegressionModel.IsProblemDataCompatible(this, problemData, out errorMessage);
+    }
+
+    public override bool IsProblemDataCompatible(IDataAnalysisProblemData problemData, out string errorMessage) {
+      if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null.");
+
+      var regressionProblemData = problemData as IRegressionProblemData;
+      if (regressionProblemData != null)
+        return IsProblemDataCompatible(regressionProblemData, out errorMessage);
+
+      var classificationProblemData = problemData as IClassificationProblemData;
+      if (classificationProblemData != null)
+        return IsProblemDataCompatible(classificationProblemData, out errorMessage);
+
+      throw new ArgumentException("The problem data is not compatible with this neural network. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
+    }
+
     public IRegressionSolution CreateRegressionSolution(IRegressionProblemData problemData) {
       return new NeuralNetworkRegressionSolution(this, new RegressionProblemData(problemData));

stable/HeuristicLab.Algorithms.DataAnalysis/3.4/RandomForest/RandomForestModel.cs

@@ -286 +286 @@
     }
 
+    public bool IsProblemDataCompatible(IRegressionProblemData problemData, out string errorMessage) {
+      return RegressionModel.IsProblemDataCompatible(this, problemData, out errorMessage);
+    }
+
+    public override bool IsProblemDataCompatible(IDataAnalysisProblemData problemData, out string errorMessage) {
+      if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null.");
+
+      var regressionProblemData = problemData as IRegressionProblemData;
+      if (regressionProblemData != null)
+        return IsProblemDataCompatible(regressionProblemData, out errorMessage);
+
+      var classificationProblemData = problemData as IClassificationProblemData;
+      if (classificationProblemData != null)
+        return IsProblemDataCompatible(classificationProblemData, out errorMessage);
+
+      throw new ArgumentException("The problem data is not compatible with this random forest. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
+    }
+
     public static RandomForestModel CreateRegressionModel(IRegressionProblemData problemData, int nTrees, double r, double m, int seed,
       out double rmsError, out double outOfBagRmsError, out double avgRelError, out double outOfBagAvgRelError) {

stable/HeuristicLab.Algorithms.DataAnalysis/3.4/SupportVectorMachine/SupportVectorMachineModel.cs

@@ -126 +126 @@
       return new SupportVectorRegressionSolution(this, new RegressionProblemData(problemData));
     }
-    #endregion
+
+    public bool IsProblemDataCompatible(IRegressionProblemData problemData, out string errorMessage) {
+      return RegressionModel.IsProblemDataCompatible(this, problemData, out errorMessage);
+    }
+    #endregion
+
+    public override bool IsProblemDataCompatible(IDataAnalysisProblemData problemData, out string errorMessage) {
+      if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null.");
+
+      var regressionProblemData = problemData as IRegressionProblemData;
+      if (regressionProblemData != null)
+        return IsProblemDataCompatible(regressionProblemData, out errorMessage);
+
+      var classificationProblemData = problemData as IClassificationProblemData;
+      if (classificationProblemData != null)
+        return IsProblemDataCompatible(classificationProblemData, out errorMessage);
+
+      throw new ArgumentException("The problem data is not compatible with this SVM. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
+    }
 
     #region IClassificationModel Members
@@ -153 +171 @@
     }
     #endregion
+
     private IEnumerable<double> GetEstimatedValuesHelper(IDataset dataset, IEnumerable<int> rows) {
       // calculate predictions for the currently requested rows

stable/HeuristicLab.Algorithms.DataAnalysis/3.4/kMeans/KMeansClusteringModel.cs

@@ -20 +20 @@
 #endregion
 
+using System;
 using System.Collections.Generic;
 using System.Drawing;
@@ -34 +35 @@
   [StorableClass]
   [Item("KMeansClusteringModel", "Represents a k-Means clustering model.")]
-  public sealed class KMeansClusteringModel : NamedItem, IClusteringModel {
+  public sealed class KMeansClusteringModel : DataAnalysisModel, IClusteringModel {
     public static new Image StaticItemImage {
       get { return HeuristicLab.Common.Resources.VSImageLibrary.Function; }
     }
 
-    public IEnumerable<string> VariablesUsedForPrediction {
+    public override IEnumerable<string> VariablesUsedForPrediction {
       get { return allowedInputVariables; }
     }
@@ -84 +85 @@
     }
 
+    public override bool IsProblemDataCompatible(IDataAnalysisProblemData problemData, out string errorMessage) {
+      if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null.");
+      return IsDatasetCompatible(problemData.Dataset, out errorMessage);
+    }
+
 
     public IEnumerable<int> GetClusterValues(IDataset dataset, IEnumerable<int> rows) {

stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationModel.cs

@@ -74 +74 @@
     }
 
+    public virtual bool IsProblemDataCompatible(IClassificationProblemData problemData, out string errorMessage) {
+      return ClassificationModel.IsProblemDataCompatible(this, problemData, out errorMessage);
+    }
+
+    public override bool IsProblemDataCompatible(IDataAnalysisProblemData problemData, out string errorMessage) {
+      if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null.");
+      var classificationProblemData = problemData as IClassificationProblemData;
+      if (classificationProblemData == null)
+        throw new ArgumentException("The problem data is not compatible with this classification model. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
+      return IsProblemDataCompatible(classificationProblemData, out errorMessage);
+    }
+
     #region events
     public event EventHandler TargetVariableChanged;

stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SymbolicRegressionModel.cs

@@ -83 +83 @@
     }
 
+    public virtual bool IsProblemDataCompatible(IRegressionProblemData problemData, out string errorMessage) {
+      return RegressionModel.IsProblemDataCompatible(this, problemData, out errorMessage);
+    }
+
+    public override bool IsProblemDataCompatible(IDataAnalysisProblemData problemData, out string errorMessage) {
+      if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null.");
+      var regressionProblemData = problemData as IRegressionProblemData;
+      if (regressionProblemData == null)
+        throw new ArgumentException("The problem data is not compatible with this symbolic regression model. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
+      return IsProblemDataCompatible(regressionProblemData, out errorMessage);
+    }
+
     #region events
     public event EventHandler TargetVariableChanged;

stable/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/SymbolicDataAnalysisModel.cs

@@ -34 +34 @@
   /// </summary>
   [StorableClass]
-  public abstract class SymbolicDataAnalysisModel : NamedItem, ISymbolicDataAnalysisModel {
+  public abstract class SymbolicDataAnalysisModel : DataAnalysisModel, ISymbolicDataAnalysisModel {
     public static new Image StaticItemImage {
       get { return HeuristicLab.Common.Resources.VSImageLibrary.Function; }
@@ -59 +59 @@
     }
 
-    public IEnumerable<string> VariablesUsedForPrediction {
+    public override IEnumerable<string> VariablesUsedForPrediction {
       get {
         var variables =

stable/HeuristicLab.Problems.DataAnalysis.Trading/3.4/ProblemData.cs

@@ -1650 +1650 @@
       OnChanged();
     }
-
-    public override void AdjustProblemDataProperties(IDataAnalysisProblemData problemData) {
-      var data = problemData as ProblemData;
-      if (data == null) throw new ArgumentException("The problem data is not a problem data set for trading. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
-
-      string errorMessage;
-      if (!data.IsProblemDataCompatible(this, out errorMessage)) {
-        throw new InvalidOperationException(errorMessage);
-      }
-
-      base.AdjustProblemDataProperties(data);
-
-      var toDelete = PriceChangeVariableParameter.ValidValues.ToList();
-      foreach (var entry in data.PriceChangeVariableParameter.ValidValues) {
-        if (toDelete.Any(x => x.Value == entry.Value)) {
-          toDelete.RemoveAll(x => x.Value == entry.Value);
-        } else {
-          PriceChangeVariableParameter.ValidValues.Add(new StringValue(entry.Value));
-        }
-      }
-      PriceChangeVariableParameter.Value =
-        PriceChangeVariableParameter.ValidValues.Single(v => v.Value == data.PriceChangeVariable);
-
-      foreach (var varToDelete in toDelete) PriceChangeVariableParameter.ValidValues.Remove(varToDelete);
-
-      TransactionCostsParameter.Value.Value = data.TransactionCosts;
-
-      OnChanged();
-    }
   }
 }

stable/HeuristicLab.Problems.DataAnalysis.Trading/3.4/Symbolic/Model.cs

@@ -20 +20 @@
 #endregion
 
+using System;
 using System.Collections.Generic;
 using System.Linq;
@@ -53 +54 @@
     }
 
+    public override bool IsProblemDataCompatible(IDataAnalysisProblemData problemData, out string errorMessage) {
+      if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null.");
+      return IsDatasetCompatible(problemData.Dataset, out errorMessage);
+    }
+
+
     // Transforms an enumerable of real values to an enumerable of trading signals (buy(1) / hold(0) / sell(-1))
     public static IEnumerable<double> GetSignals(IEnumerable<double> xs) {

stable/HeuristicLab.Problems.DataAnalysis.Views/3.4/Solution Views/DataAnalysisSolutionView.cs

@@ -141 +141 @@
 
         var solution = (IDataAnalysisSolution)Content.Clone();
-        problemData.AdjustProblemDataProperties(solution.ProblemData);
-
         solution.ProblemData = problemData;
         if (!solution.Name.EndsWith(" with loaded problemData"))
@@ -231 +229 @@
 
       try {
-        problemData.AdjustProblemDataProperties(Content.ProblemData);
         Content.ProblemData = problemData;
 

stable/HeuristicLab.Problems.DataAnalysis/3.4/Dataset.cs

@@ -167 +167 @@
       }
     }
+
+    public bool ContainsVariable(string variableName) {
+      return variableValues.ContainsKey(variableName);
+    }
     public IEnumerable<string> DoubleVariables {
       get { return variableValues.Where(p => p.Value is IList<double>).Select(p => p.Key); }

stable/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ClassificationModel.cs

@@ -66 +66 @@
     public abstract IClassificationSolution CreateClassificationSolution(IClassificationProblemData problemData);
 
+    public virtual bool IsProblemDataCompatible(IClassificationProblemData problemData, out string errorMessage) {
+      return IsProblemDataCompatible(this, problemData, out errorMessage);
+    }
+
+    public override bool IsProblemDataCompatible(IDataAnalysisProblemData problemData, out string errorMessage) {
+      if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null.");
+      var classificationProblemData = problemData as IClassificationProblemData;
+      if (classificationProblemData == null)
+        throw new ArgumentException("The problem data is not compatible with this classification model. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
+      return IsProblemDataCompatible(classificationProblemData, out errorMessage);
+    }
+
+    public static bool IsProblemDataCompatible(IClassificationModel model, IClassificationProblemData problemData, out string errorMessage) {
+      if (model == null) throw new ArgumentNullException("model", "The provided model is null.");
+      if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null.");
+      errorMessage = string.Empty;
+
+      if (model.TargetVariable != problemData.TargetVariable)
+        errorMessage = string.Format("The target variable of the model {0} does not match the target variable of the problemData {1}.", model.TargetVariable, problemData.TargetVariable);
+
+      var evaluationErrorMessage = string.Empty;
+      var datasetCompatible = model.IsDatasetCompatible(problemData.Dataset, out evaluationErrorMessage);
+      if (!datasetCompatible)
+        errorMessage += evaluationErrorMessage;
+
+      return string.IsNullOrEmpty(errorMessage);
+    }
+
     #region events
     public event EventHandler TargetVariableChanged;

stable/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ClassificationProblemData.cs

@@ -467 +467 @@
     }
     #endregion
-
-    protected override bool IsProblemDataCompatible(IDataAnalysisProblemData problemData, out string errorMessage) {
-      if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null.");
-      IClassificationProblemData classificationProblemData = problemData as IClassificationProblemData;
-      if (classificationProblemData == null)
-        throw new ArgumentException("The problem data is no classification problem data. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
-
-      var returnValue = base.IsProblemDataCompatible(classificationProblemData, out errorMessage);
-      //check targetVariable
-      if (classificationProblemData.InputVariables.All(var => var.Value != TargetVariable)) {
-        errorMessage = string.Format("The target variable {0} is not present in the new problem data.", TargetVariable)
-                       + Environment.NewLine + errorMessage;
-        return false;
-      }
-
-      var newClassValues = classificationProblemData.Dataset.GetDoubleValues(TargetVariable).Distinct().OrderBy(x => x);
-      if (!newClassValues.SequenceEqual(ClassValues)) {
-        errorMessage = errorMessage + string.Format("The class values differ in the provided classification problem data.");
-        returnValue = false;
-      }
-
-      var newPositivieClassName = classificationProblemData.PositiveClass;
-      if (newPositivieClassName != PositiveClass) {
-        errorMessage = errorMessage + string.Format("The positive class differs in the provided classification problem data.");
-        returnValue = false;
-      }
-
-      return returnValue;
-    }
-
-    public override void AdjustProblemDataProperties(IDataAnalysisProblemData problemData) {
-      if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null.");
-      ClassificationProblemData classificationProblemData = problemData as ClassificationProblemData;
-      if (classificationProblemData == null)
-        throw new ArgumentException("The problem data is not a classification problem data. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
-
-      base.AdjustProblemDataProperties(problemData);
-      TargetVariable = classificationProblemData.TargetVariable;
-      for (int i = 0; i < classificationProblemData.ClassNames.Count(); i++)
-        ClassNamesParameter.Value[i, 0] = classificationProblemData.ClassNames.ElementAt(i);
-
-      PositiveClass = classificationProblemData.PositiveClass;
-
-      for (int i = 0; i < Classes; i++) {
-        for (int j = 0; j < Classes; j++) {
-          ClassificationPenaltiesParameter.Value[i, j] = classificationProblemData.GetClassificationPenalty(ClassValuesCache[i], ClassValuesCache[j]);
-        }
-      }
-    }
   }
 }

stable/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ClassificationSolutionBase.cs

@@ -20 +20 @@
 #endregion
 
+using System;
 using System.Collections.Generic;
 using System.Linq;
@@ -44 +45 @@
     public new IClassificationProblemData ProblemData {
       get { return (IClassificationProblemData)base.ProblemData; }
-      set { base.ProblemData = value; }
+      set {
+        if (value == null) throw new ArgumentNullException("The problemData must not be null.");
+        string errorMessage = string.Empty;
+        if (!Model.IsProblemDataCompatible(value, out errorMessage)) throw new ArgumentException(errorMessage);
+
+        base.ProblemData = value;
+      }
     }
 

stable/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/ConstantModel.cs

@@ -83 +83 @@
     }
 
+    public virtual bool IsProblemDataCompatible(IClassificationProblemData problemData, out string errorMessage) {
+      return ClassificationModel.IsProblemDataCompatible(this, problemData, out errorMessage);
+    }
+
+    public override bool IsProblemDataCompatible(IDataAnalysisProblemData problemData, out string errorMessage) {
+      if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null.");
+
+      var regressionProblemData = problemData as IRegressionProblemData;
+      if (regressionProblemData != null)
+        return IsProblemDataCompatible(regressionProblemData, out errorMessage);
+
+      var classificationProblemData = problemData as IClassificationProblemData;
+      if (classificationProblemData != null)
+        return IsProblemDataCompatible(classificationProblemData, out errorMessage);
+
+      throw new ArgumentException("The problem data is compatible with this model. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
+    }
+
     #region IStringConvertibleValue
     public bool ReadOnly { get; private set; }

stable/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/DataAnalysisModel.cs

@@ -20 +20 @@
 #endregion
 
+using System;
 using System.Collections.Generic;
 using HeuristicLab.Common;
@@ -38 +39 @@
 
     public abstract IEnumerable<string> VariablesUsedForPrediction { get; }
+
+    public virtual bool IsDatasetCompatible(IDataset dataset, out string errorMessage) {
+      if (dataset == null) throw new ArgumentNullException("dataset", "The provided dataset is null.");
+      return IsDatasetCompatible(this, dataset, out errorMessage);
+    }
+
+    public abstract bool IsProblemDataCompatible(IDataAnalysisProblemData problemData, out string errorMessage);
+
+    public static bool IsDatasetCompatible(IDataAnalysisModel model, IDataset dataset, out string errorMessage) {
+      if(model == null) throw new ArgumentNullException("model", "The provided model is null.");
+      if (dataset == null) throw new ArgumentNullException("dataset", "The provided dataset is null.");
+      errorMessage = string.Empty;
+
+      foreach (var variable in model.VariablesUsedForPrediction) {
+        if (!dataset.ContainsVariable(variable)) {
+          if (string.IsNullOrEmpty(errorMessage)) {
+            errorMessage = "The following variables must be present in the dataset for model evaluation:";
+          }
+          errorMessage += System.Environment.NewLine + " " + variable;
+        }
+      }
+
+      return string.IsNullOrEmpty(errorMessage);
+    }
   }
 }

stable/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/DataAnalysisProblemData.cs

@@ -207 +207 @@
       if (listeners != null) listeners(this, EventArgs.Empty);
     }
-
-    protected virtual bool IsProblemDataCompatible(IDataAnalysisProblemData problemData, out string errorMessage) {
-      errorMessage = string.Empty;
-      if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null.");
-
-      //check allowed input variables
-      StringBuilder message = new StringBuilder();
-      var variables = new HashSet<string>(problemData.InputVariables.Select(x => x.Value));
-      foreach (var item in AllowedInputVariables) {
-        if (!variables.Contains(item))
-          message.AppendLine("Input variable '" + item + "' is not present in the new problem data.");
-      }
-
-      if (message.Length != 0) {
-        errorMessage = message.ToString();
-        return false;
-      }
-      return true;
-
-    }
-
-    public virtual void AdjustProblemDataProperties(IDataAnalysisProblemData problemData) {
-      DataAnalysisProblemData data = problemData as DataAnalysisProblemData;
-      if (data == null) throw new ArgumentException("The problem data is not a data analysis problem data. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
-
-      string errorMessage;
-      if (!data.IsProblemDataCompatible(this, out errorMessage)) {
-        throw new InvalidOperationException(errorMessage);
-      }
-
-      foreach (var inputVariable in InputVariables) {
-        var variable = data.InputVariables.FirstOrDefault(i => i.Value == inputVariable.Value);
-        InputVariables.SetItemCheckedState(inputVariable, variable != null && data.InputVariables.ItemChecked(variable));
-      }
-    }
   }
 }

stable/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/DataAnalysisSolution.cs

@@ -58 +58 @@
       get { return (IDataAnalysisProblemData)this[ProblemDataResultName].Value; }
       set {
-        if (this[ProblemDataResultName].Value != value) {
-          if (value != null) {
-            ProblemData.Changed -= new EventHandler(ProblemData_Changed);
-            this[ProblemDataResultName].Value = value;
-            ProblemData.Changed += new EventHandler(ProblemData_Changed);
-            OnProblemDataChanged();
-          }
-        }
+        if (value == null) throw new ArgumentNullException("The problemData must not be null.");
+        if (this[ProblemDataResultName].Value == value) return;
+        string errorMessage = string.Empty;
+        if (!Model.IsProblemDataCompatible(value, out errorMessage)) throw new ArgumentException(errorMessage);
+
+        ProblemData.Changed -= new EventHandler(ProblemData_Changed);
+        this[ProblemDataResultName].Value = value;
+        ProblemData.Changed += new EventHandler(ProblemData_Changed);
+        OnProblemDataChanged();
       }
     }

stable/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Regression/RegressionModel.cs

@@ -67 +67 @@
     public abstract IRegressionSolution CreateRegressionSolution(IRegressionProblemData problemData);
 
+    public virtual bool IsProblemDataCompatible(IRegressionProblemData problemData, out string errorMessage) {
+      return IsProblemDataCompatible(this, problemData, out errorMessage);
+    }
+
+    public override bool IsProblemDataCompatible(IDataAnalysisProblemData problemData, out string errorMessage) {
+      if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null.");
+      var regressionProblemData = problemData as IRegressionProblemData;
+      if (regressionProblemData == null)
+        throw new ArgumentException("The problem data is not compatible with this regression model. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
+      return IsProblemDataCompatible(regressionProblemData, out errorMessage);
+    }
+
+    public static bool IsProblemDataCompatible(IRegressionModel model, IRegressionProblemData problemData, out string errorMessage) {
+      if (model == null) throw new ArgumentNullException("model", "The provided model is null.");
+      if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null.");
+      errorMessage = string.Empty;
+
+      if (model.TargetVariable != problemData.TargetVariable)
+        errorMessage = string.Format("The target variable of the model {0} does not match the target variable of the problemData {1}.", model.TargetVariable, problemData.TargetVariable);
+
+      var evaluationErrorMessage = string.Empty;
+      var datasetCompatible = model.IsDatasetCompatible(problemData.Dataset, out evaluationErrorMessage);
+      if (!datasetCompatible)
+        errorMessage += evaluationErrorMessage;
+
+      return string.IsNullOrEmpty(errorMessage);
+    }
+
     #region events
     public event EventHandler TargetVariableChanged;

stable/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Regression/RegressionProblemData.cs

@@ -161 +161 @@
       OnChanged();
     }
-
-    protected override bool IsProblemDataCompatible(IDataAnalysisProblemData problemData, out string errorMessage) {
-      if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null.");
-      IRegressionProblemData regressionProblemData = problemData as IRegressionProblemData;
-      if (regressionProblemData == null)
-        throw new ArgumentException("The problem data is not a regression problem data. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
-
-      var returnValue = base.IsProblemDataCompatible(problemData, out errorMessage);
-      return returnValue;
-    }
-
-    public override void AdjustProblemDataProperties(IDataAnalysisProblemData problemData) {
-      if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null.");
-      RegressionProblemData regressionProblemData = problemData as RegressionProblemData;
-      if (regressionProblemData == null)
-        throw new ArgumentException("The problem data is not a regression problem data. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
-
-      base.AdjustProblemDataProperties(problemData);
-    }
   }
 }

stable/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Regression/RegressionSolutionBase.cs

@@ -70 +70 @@
     public new IRegressionProblemData ProblemData {
       get { return (IRegressionProblemData)base.ProblemData; }
-      set { base.ProblemData = value; }
+      set {
+        if (value == null) throw new ArgumentNullException("The problemData must not be null.");
+        string errorMessage = string.Empty;
+        if (!Model.IsProblemDataCompatible(value, out errorMessage)) throw new ArgumentException(errorMessage);
+
+        base.ProblemData = value;
+      }
     }
 

stable/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/TimeSeriesPrognosis/TimeSeriesPrognosisProblemData.cs

@@ -1620 +1620 @@
       OnChanged();
     }
-
-    protected override bool IsProblemDataCompatible(IDataAnalysisProblemData problemData, out string errorMessage) {
-      if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null.");
-      ITimeSeriesPrognosisProblemData timeseriesProblemData = problemData as ITimeSeriesPrognosisProblemData;
-      if (timeseriesProblemData == null)
-        throw new ArgumentException("The problem data is not a time-series problem data. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
-
-      var returnValue = base.IsProblemDataCompatible(problemData, out errorMessage);
-      //check targetVariable
-      if (problemData.InputVariables.All(var => var.Value != TargetVariable)) {
-        errorMessage = string.Format("The target variable {0} is not present in the new problem data.", TargetVariable)
-                       + Environment.NewLine + errorMessage;
-        return false;
-      }
-      return returnValue;
-    }
-
-    public override void AdjustProblemDataProperties(IDataAnalysisProblemData problemData) {
-      TimeSeriesPrognosisProblemData timeSeriesProblemData = problemData as TimeSeriesPrognosisProblemData;
-      if (timeSeriesProblemData == null)
-        throw new ArgumentException("The problem data is not a timeseries problem data. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
-
-      var trainingDataStart = TrainingIndices.First();
-
-      base.AdjustProblemDataProperties(problemData);
-
-      TestPartition.Start = trainingDataStart;
-
-      TrainingHorizon = timeSeriesProblemData.TrainingHorizon;
-      TestHorizon = timeSeriesProblemData.TestHorizon;
-    }
-
   }
 }

stable/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/Classification/IClassificationModel.cs

@@ -31 +31 @@
     IEnumerable<double> GetEstimatedClassValues(IDataset dataset, IEnumerable<int> rows);
     IClassificationSolution CreateClassificationSolution(IClassificationProblemData problemData);
+    bool IsProblemDataCompatible(IClassificationProblemData problemData, out string errorMessage);
     string TargetVariable { get; set; }
     event EventHandler TargetVariableChanged;

stable/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/IDataAnalysisModel.cs

@@ -30 +30 @@
   public interface IDataAnalysisModel : INamedItem {
     IEnumerable<string> VariablesUsedForPrediction { get; }
+    bool IsDatasetCompatible(IDataset dataset, out string errorMessage);
+    bool IsProblemDataCompatible(IDataAnalysisProblemData problemData, out string errorMessage);
   }
 }

stable/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/IDataAnalysisProblemData.cs

@@ -49 +49 @@
 
     event EventHandler Changed;
-
-    void AdjustProblemDataProperties(IDataAnalysisProblemData problemData);
   }
 }

stable/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/IDataset.cs

@@ -33 +33 @@
     IEnumerable<string> DateTimeVariables { get; }
 
+    bool ContainsVariable(string variablename);
     bool VariableHasType<T>(string variableName);
 

stable/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/Regression/IRegressionModel.cs

@@ -31 +31 @@
     IEnumerable<double> GetEstimatedValues(IDataset dataset, IEnumerable<int> rows);
     IRegressionSolution CreateRegressionSolution(IRegressionProblemData problemData);
+    bool IsProblemDataCompatible(IRegressionProblemData problemData, out string errorMessage);
     string TargetVariable { get; set; }
     event EventHandler TargetVariableChanged;