Changeset 15105 for trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees

Timestamp:

07/01/17 10:41:20 (7 years ago)

Author:

gkronber

Message:

#2690 added a model view for GBT models and renamed the existing evaluation view accordingly. Deleted GBT solution view because it is not necessary anymore.

Location:

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees

Files:

• GradientBoostedTreesModel.cs (modified) (1 diff)
• RegressionTreeModel.cs (modified) (2 diffs)

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesModel.cs

@@ -31 +31 @@
 namespace HeuristicLab.Algorithms.DataAnalysis {
   [StorableClass]
-  [Item("Gradient boosted tree model", "")]
+  [Item("Gradient boosted trees model", "")]
   // this is essentially a collection of weighted regression models
   public sealed class GradientBoostedTreesModel : RegressionModel, IGradientBoostedTreesModel {

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/RegressionTreeModel.cs

@@ -219 +219 @@
     /// <returns>A new symbolic regression solution which matches the tree model</returns>
     public ISymbolicRegressionSolution CreateSymbolicRegressionSolution(IRegressionProblemData problemData) {
+      return CreateSymbolicRegressionModel().CreateRegressionSolution(problemData);
+    }
+
+    /// <summary>
+    /// Transforms the tree model to a symbolic regression model
+    /// </summary>
+    /// <returns>A new symbolic regression model which matches the tree model</returns>
+    public SymbolicRegressionModel CreateSymbolicRegressionModel() {
       var rootSy = new ProgramRootSymbol();
       var startSy = new StartSymbol();
@@ -228 +236 @@
       var rootNode = rootSy.CreateTreeNode();
       rootNode.AddSubtree(startNode);
-      var model = new SymbolicRegressionModel(TargetVariable, new SymbolicExpressionTree(rootNode), new SymbolicDataAnalysisExpressionTreeLinearInterpreter());
-      return model.CreateRegressionSolution(problemData);
+      return new SymbolicRegressionModel(TargetVariable, new SymbolicExpressionTree(rootNode), new SymbolicDataAnalysisExpressionTreeLinearInterpreter());
     }