Changeset 16243 for trunk/HeuristicLab.Algorithms.DataAnalysis/3.4

Timestamp:

10/19/18 13:27:06 (6 years ago)

Author:

mkommend

Message:

#2955: Added IsProblemDataCompatible and IsDatasetCompatible to all DataAnalysisModels.

Location:

trunk/HeuristicLab.Algorithms.DataAnalysis/3.4

Files:

• NearestNeighbour/NearestNeighbourModel.cs (modified) (1 diff)
• NeuralNetwork/NeuralNetworkEnsembleModel.cs (modified) (1 diff)
• NeuralNetwork/NeuralNetworkModel.cs (modified) (1 diff)
• RandomForest/RandomForestModel.cs (modified) (1 diff)
• SupportVectorMachine/SupportVectorMachineModel.cs (modified) (2 diffs)
• kMeans/KMeansClusteringModel.cs (modified) (3 diffs)

trunk/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 a regression nor a classification problem data. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
+    }
+
     IRegressionSolution IRegressionModel.CreateRegressionSolution(IRegressionProblemData problemData) {
       return new NearestNeighbourRegressionSolution(this, new RegressionProblemData(problemData));

trunk/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 a regression nor a classification problem data. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
+    }
+
     public IRegressionSolution CreateRegressionSolution(IRegressionProblemData problemData) {
       return new NeuralNetworkEnsembleRegressionSolution(this, new RegressionEnsembleProblemData(problemData));

trunk/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 a regression nor a classification problem data. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
+    }
+
     public IRegressionSolution CreateRegressionSolution(IRegressionProblemData problemData) {
       return new NeuralNetworkRegressionSolution(this, new RegressionProblemData(problemData));

trunk/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 a regression nor a classification problem data. 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) {

trunk/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 a regression nor a classification problem data. 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

trunk/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) {