Changeset 155 for trunk/sources/HeuristicLab.StructureIdentification/Evaluation

Timestamp:

04/22/08 18:05:14 (17 years ago)

Author:

gkronber

Message:

merged FunctionsAndStructIdRefactoring-branch (r142, r143, r144, r145, r146, r147, r148, r149, r152, r153) back into the trunk (ticket #112)

Location:

trunk/sources/HeuristicLab.StructureIdentification/Evaluation

Files:

• CoefficientOfDeterminationEvaluator.cs (modified) (2 diffs)
• EarlyStoppingMeanSquaredErrorEvaluator.cs (modified) (2 diffs)
• GPEvaluatorBase.cs (modified) (2 diffs)
• MeanSquaredErrorEvaluator.cs (modified) (2 diffs)
• VarianceAccountedForEvaluator.cs (modified) (2 diffs)

trunk/sources/HeuristicLab.StructureIdentification/Evaluation/CoefficientOfDeterminationEvaluator.cs

@@ -34 +34 @@
     public override string Description {
       get {
-        return @"Applies 'OperatorTree' to all samples of 'Dataset' and calculates
+        return @"Evaluates 'FunctionTree' for all samples of 'Dataset' and calculates
 the 'coefficient of determination' of estimated values vs. real values of 'TargetVariable'.";
       }
@@ -43 +43 @@
     }
 
-    public override double Evaluate(IScope scope, IFunction function, int targetVariable, Dataset dataset) {
+    public override double Evaluate(IScope scope, IFunctionTree functionTree, int targetVariable, Dataset dataset) {
       double errorsSquaredSum = 0.0;
       double originalDeviationTotalSumOfSquares = 0.0;
       double targetMean = dataset.GetMean(targetVariable);
       for(int sample = 0; sample < dataset.Rows; sample++) {
-        double estimated = function.Evaluate(dataset, sample);
+        double estimated = functionTree.Evaluate(dataset, sample);
         double original = dataset.GetValue(sample, targetVariable);
         if(!double.IsNaN(original) && !double.IsInfinity(original)) {

trunk/sources/HeuristicLab.StructureIdentification/Evaluation/EarlyStoppingMeanSquaredErrorEvaluator.cs

@@ -34 +34 @@
     public override string Description {
       get {
-        return @"Evaluates 'OperatorTree' for all samples of the dataset and calculates the mean-squared-error
+        return @"Evaluates 'FunctionTree' for all samples of the dataset and calculates the mean-squared-error
 for the estimated values vs. the real values of 'TargetVariable'.
 This operator stops the computation as soon as an upper limit for the mean-squared-error is reached.";
@@ -45 +45 @@
     }
 
-    public override double Evaluate(IScope scope, IFunction function, int targetVariable, Dataset dataset) {
+    public override double Evaluate(IScope scope, IFunctionTree functionTree, int targetVariable, Dataset dataset) {
       double qualityLimit = GetVariableValue<DoubleData>("QualityLimit", scope, false).Data;
       double errorsSquaredSum = 0;
       double targetMean = dataset.GetMean(targetVariable);
       for(int sample = 0; sample < dataset.Rows; sample++) {
-        double estimated = function.Evaluate(dataset, sample);
+        double estimated = functionTree.Evaluate(dataset, sample);
         double original = dataset.GetValue(sample, targetVariable);
         if(double.IsNaN(estimated) || double.IsInfinity(estimated)) {

trunk/sources/HeuristicLab.StructureIdentification/Evaluation/GPEvaluatorBase.cs

@@ -36 +36 @@
     public GPEvaluatorBase()
       : base() {
-      AddVariableInfo(new VariableInfo("OperatorTree", "The function tree that should be evaluated", typeof(IFunction), VariableKind.In));
+      AddVariableInfo(new VariableInfo("FunctionTree", "The function tree that should be evaluated", typeof(IFunctionTree), VariableKind.In));
       AddVariableInfo(new VariableInfo("Dataset", "Dataset with all samples on which to apply the function", typeof(Dataset), VariableKind.In));
       AddVariableInfo(new VariableInfo("TargetVariable", "Index of the column of the dataset that holds the target variable", typeof(IntData), VariableKind.In));
@@ -46 +46 @@
       int targetVariable = GetVariableValue<IntData>("TargetVariable", scope, true).Data;
       Dataset dataset = GetVariableValue<Dataset>("Dataset", scope, true);
-      IFunction function = GetVariableValue<IFunction>("OperatorTree", scope, true);
+      IFunctionTree functionTree = GetVariableValue<IFunctionTree>("FunctionTree", scope, true);
       this.maximumPunishment = GetVariableValue<DoubleData>("PunishmentFactor", scope, true).Data * dataset.GetRange(targetVariable);
 
-      double result = Evaluate(scope, function, targetVariable, dataset);
+      double result = Evaluate(scope, functionTree, targetVariable, dataset);
       scope.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName("Quality"), new DoubleData(result)));
       return null;
     }
 
-    public abstract double Evaluate(IScope scope, IFunction function, int targetVariable, Dataset dataset);
+    public abstract double Evaluate(IScope scope, IFunctionTree functionTree, int targetVariable, Dataset dataset);
   }
 }

trunk/sources/HeuristicLab.StructureIdentification/Evaluation/MeanSquaredErrorEvaluator.cs

@@ -34 +34 @@
     public override string Description {
       get {
-        return @"Evaluates 'OperatorTree' for all samples of 'DataSet' and calculates the mean-squared-error
+        return @"Evaluates 'FunctionTree' for all samples of 'DataSet' and calculates the mean-squared-error
 for the estimated values vs. the real values of 'TargetVariable'.";
       }
@@ -43 +43 @@
     }
 
-    public override double Evaluate(IScope scope, IFunction function, int targetVariable, Dataset dataset) {
+    public override double Evaluate(IScope scope, IFunctionTree functionTree, int targetVariable, Dataset dataset) {
       double errorsSquaredSum = 0;
       double targetMean = dataset.GetMean(targetVariable);
       for(int sample = 0; sample < dataset.Rows; sample++) {
-        double estimated = function.Evaluate(dataset, sample);
+
+        double estimated = functionTree.Evaluate(dataset, sample);
         double original = dataset.GetValue(sample, targetVariable);
         if(double.IsNaN(estimated) || double.IsInfinity(estimated)) {

trunk/sources/HeuristicLab.StructureIdentification/Evaluation/VarianceAccountedForEvaluator.cs

@@ -34 +34 @@
     public override string Description {
       get {
-        return @"Evaluates 'OperatorTree' for all samples of 'DataSet' and calculates 
+        return @"Evaluates 'FunctionTree' for all samples of 'DataSet' and calculates 
 the variance-accounted-for quality measure for the estimated values vs. the real values of 'TargetVariable'.
 
@@ -53 +53 @@
 
 
-    public override double Evaluate(IScope scope, IFunction function, int targetVariable, Dataset dataset) {
+    public override double Evaluate(IScope scope, IFunctionTree functionTree, int targetVariable, Dataset dataset) {
       double[] errors = new double[dataset.Rows];
       double[] originalTargetVariableValues = new double[dataset.Rows];
       double targetMean = dataset.GetMean(targetVariable);
       for(int sample = 0; sample < dataset.Rows; sample++) {
-        double estimated = function.Evaluate(dataset, sample);
+        double estimated = functionTree.Evaluate(dataset, sample);
         double original = dataset.GetValue(sample, targetVariable);
         if(!double.IsNaN(original) && !double.IsInfinity(original)) {