Changeset 2351 for trunk/sources/HeuristicLab.Modeling/3.2/SimpleConfusionMatrixEvaluator.cs

Timestamp:

09/14/09 17:30:02 (15 years ago)

Author:

gkronber

Message:

Worked on SVM classification engine. #625

File:

• trunk/sources/HeuristicLab.Modeling/3.2/SimpleConfusionMatrixEvaluator.cs (moved) (moved from trunk/sources/HeuristicLab.GP.StructureIdentification.Classification/3.3/ConfusionMatrixEvaluator.cs) (3 diffs)

trunk/sources/HeuristicLab.Modeling/3.2/SimpleConfusionMatrixEvaluator.cs

@@ -23 +23 @@
 using HeuristicLab.Data;
 
-namespace HeuristicLab.GP.StructureIdentification.Classification {
-  public class ConfusionMatrixEvaluator : GPClassificationEvaluatorBase {
+namespace HeuristicLab.Modeling {
+  public class SimpleConfusionMatrixEvaluator : OperatorBase {
     public override string Description {
       get {
@@ -31 +31 @@
     }
 
-    public ConfusionMatrixEvaluator()
+    public SimpleConfusionMatrixEvaluator()
       : base() {
+      AddVariableInfo(new VariableInfo("Values", "Original and predicted target values generated by a model", typeof(DoubleMatrixData), VariableKind.In));
       AddVariableInfo(new VariableInfo("ConfusionMatrix", "The confusion matrix of the model", typeof(IntMatrixData), VariableKind.New));
     }
 
-    public override void Evaluate(IScope scope, ITreeEvaluator evaluator, HeuristicLab.DataAnalysis.Dataset dataset, int targetVariable, double[] classes, double[] thresholds, int start, int end) {
+    public override IOperation Apply(IScope scope) {
+      double[,] values = GetVariableValue<DoubleMatrixData>("Values", scope, true).Data;
+      int[,] confusionMatrix = Calculate(values);
       IntMatrixData matrix = GetVariableValue<IntMatrixData>("ConfusionMatrix", scope, false, false);
       if (matrix == null) {
-        matrix = new IntMatrixData(new int[classes.Length, classes.Length]);
+        matrix = new IntMatrixData(confusionMatrix);
         scope.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName("ConfusionMatrix"), matrix));
       }
 
-      int nSamples = end - start;
-      for (int sample = start; sample < end; sample++) {
-        double est = evaluator.Evaluate(sample);
-        double origClass = dataset.GetValue(sample, targetVariable);
+      return null;
+    }
+
+    public static int[,] Calculate(double[,] values) {
+      double[] classes = SimpleAccuracyEvaluator.CalculateTargetClasses(values);
+      double[] thresholds = SimpleAccuracyEvaluator.CalculateThresholds(classes);
+      int nSamples = values.GetLength(0);
+      int[,] confusionMatrix = new int[classes.Length, classes.Length];
+      for (int sample = 0; sample < nSamples; sample++) {
+        double est = values[sample, 0];
+        double origClass = values[sample, 1];
         int estClassIndex = -1;
         // if estimation is lower than the smallest threshold value -> estimated class is the lower class
@@ -70 +80 @@
           }
         }
-        matrix.Data[origClassIndex, estClassIndex]++;
+        confusionMatrix[origClassIndex, estClassIndex]++;
       }
+      return confusionMatrix;
     }
   }