Changeset 1891 for trunk/sources/HeuristicLab.GP.StructureIdentification.Classification

Timestamp:

05/25/09 17:46:17 (16 years ago)

Author:

gkronber

Message:

Fixed #645 (Tree evaluators precompile the model for each evaluation of a row).

Location:

trunk/sources/HeuristicLab.GP.StructureIdentification.Classification/3.3

Files:

• AccuracyEvaluator.cs (modified) (2 diffs)
• ClassificationMeanSquaredErrorEvaluator.cs (modified) (1 diff)
• ConfusionMatrixEvaluator.cs (modified) (2 diffs)
• GPClassificationEvaluatorBase.cs (modified) (2 diffs)
• MulticlassOneVsOneAnalyzer.cs (modified) (1 diff)

trunk/sources/HeuristicLab.GP.StructureIdentification.Classification/3.3/AccuracyEvaluator.cs

@@ -43 +43 @@
     }
 
-    public override void Evaluate(IScope scope, ITreeEvaluator evaluator, IFunctionTree tree, Dataset dataset, int targetVariable, double[] classes, double[] thresholds, int start, int end) {
+    public override void Evaluate(IScope scope, ITreeEvaluator evaluator, Dataset dataset, int targetVariable, double[] classes, double[] thresholds, int start, int end) {
       DoubleData accuracy = GetVariableValue<DoubleData>("Accuracy", scope, false, false);
       if (accuracy == null) {
@@ -53 +53 @@
       int nCorrect = 0;
       for (int sample = start; sample < end; sample++) {
-        double est = evaluator.Evaluate(tree, sample);
+        double est = evaluator.Evaluate(sample);
         double origClass = dataset.GetValue(sample, targetVariable);
         double estClass = double.NaN;

trunk/sources/HeuristicLab.GP.StructureIdentification.Classification/3.3/ClassificationMeanSquaredErrorEvaluator.cs

@@ -43 +43 @@
     }
 
-    public override void Evaluate(IScope scope, ITreeEvaluator evaluator, IFunctionTree tree, HeuristicLab.DataAnalysis.Dataset dataset, int targetVariable, double[] classes, double[] thresholds, int start, int end) {
+    public override void Evaluate(IScope scope, ITreeEvaluator evaluator, HeuristicLab.DataAnalysis.Dataset dataset, int targetVariable, double[] classes, double[] thresholds, int start, int end) {
       double errorsSquaredSum = 0;
       for (int sample = start; sample < end; sample++) {
-        double estimated = evaluator.Evaluate(tree, sample);
+        double estimated = evaluator.Evaluate(sample);
         double original = dataset.GetValue(sample, targetVariable);
         if (!double.IsNaN(original) && !double.IsInfinity(original)) {

trunk/sources/HeuristicLab.GP.StructureIdentification.Classification/3.3/ConfusionMatrixEvaluator.cs

@@ -41 +41 @@
     }
 
-    public override void Evaluate(IScope scope, ITreeEvaluator evaluator, IFunctionTree tree, HeuristicLab.DataAnalysis.Dataset dataset, int targetVariable, double[] classes, double[] thresholds, int start, int end) {
+    public override void Evaluate(IScope scope, ITreeEvaluator evaluator, HeuristicLab.DataAnalysis.Dataset dataset, int targetVariable, double[] classes, double[] thresholds, int start, int end) {
       IntMatrixData matrix = GetVariableValue<IntMatrixData>("ConfusionMatrix", scope, false, false);
       if (matrix == null) {
@@ -50 +50 @@
       int nSamples = end - start;
       for (int sample = start; sample < end; sample++) {
-        double est = evaluator.Evaluate(tree, sample);
+        double est = evaluator.Evaluate(sample);
         double origClass = dataset.GetValue(sample, targetVariable);
         int estClassIndex = -1;

trunk/sources/HeuristicLab.GP.StructureIdentification.Classification/3.3/GPClassificationEvaluatorBase.cs

@@ -37 +37 @@
     }
 
-    public override void Evaluate(IScope scope, ITreeEvaluator evaluator, IFunctionTree tree, Dataset dataset, int targetVariable, int start, int end, bool updateTargetValues) {
+    public override void Evaluate(IScope scope, ITreeEvaluator evaluator, Dataset dataset, int targetVariable, int start, int end, bool updateTargetValues) {
 
       ItemList<DoubleData> classes = GetVariableValue<ItemList<DoubleData>>("TargetClassValues", scope, true);
@@ -48 +48 @@
       }
 
-      Evaluate(scope, evaluator, tree, dataset, targetVariable, classesArr, thresholds, start, end);
+      Evaluate(scope, evaluator, dataset, targetVariable, classesArr, thresholds, start, end);
     }
 
-    public abstract void Evaluate(IScope scope, ITreeEvaluator evaluator, IFunctionTree tree, Dataset dataset, int targetVariable, double[] classes, double[] thresholds, int start, int end);
+    public abstract void Evaluate(IScope scope, ITreeEvaluator evaluator, Dataset dataset, int targetVariable, double[] classes, double[] thresholds, int start, int end);
   }
 }

trunk/sources/HeuristicLab.GP.StructureIdentification.Classification/3.3/MulticlassOneVsOneAnalyzer.cs

@@ -86 +86 @@
         BakedTreeEvaluator evaluator = new BakedTreeEvaluator();
         evaluator.ResetEvaluator(dataset, targetVariable, trainingSamplesStart, trainingSamplesEnd, 1.0);
-
+        evaluator.PrepareForEvaluation(functionTree);
         for(int i = 0; i < (samplesEnd - samplesStart); i++) {
-          double est = evaluator.Evaluate(functionTree, i + samplesStart);
+          double est = evaluator.Evaluate(i + samplesStart);
           if(est < 0.5) {
             CastVote(votes, i, classAValue, classValues);