Changeset 13157 for trunk/sources/HeuristicLab.Algorithms.DataAnalysis

Timestamp:

11/14/15 08:10:18 (9 years ago)

Author:

gkronber

Message:

#2450 made the changes suggested by mkommend in the review. This is definitely a big improvement, thx!

Location:

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4

Files:

• GradientBoostedTrees/GradientBoostedTreesAlgorithmStatic.cs (modified) (2 diffs)
• GradientBoostedTrees/GradientBoostedTreesModel.cs (modified) (1 diff)
• GradientBoostedTrees/GradientBoostedTreesModelSurrogate.cs (modified) (3 diffs)
• GradientBoostedTrees/GradientBoostedTreesSolution.cs (added)
• GradientBoostedTrees/IGradientBoostedTreesModel.cs (added)
• HeuristicLab.Algorithms.DataAnalysis-3.4.csproj (modified) (2 diffs)

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

@@ -130 +130 @@
 
     // simple interface
-    public static IRegressionSolution TrainGbm(IRegressionProblemData problemData, ILossFunction lossFunction, int maxSize, double nu, double r, double m, int maxIterations, uint randSeed = 31415) {
+    public static GradientBoostedTreesSolution TrainGbm(IRegressionProblemData problemData, ILossFunction lossFunction, int maxSize, double nu, double r, double m, int maxIterations, uint randSeed = 31415) {
       Contract.Assert(r > 0);
       Contract.Assert(r <= 1.0);
@@ -143 +143 @@
 
       var model = state.GetModel();
-      return new RegressionSolution(model, (IRegressionProblemData)problemData.Clone());
+      return new GradientBoostedTreesSolution(model, (IRegressionProblemData)problemData.Clone());
     }
 

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

@@ -33 +33 @@
   [Item("Gradient boosted tree model", "")]
   // this is essentially a collection of weighted regression models
-  public sealed class GradientBoostedTreesModel : NamedItem, IRegressionModel {
+  public sealed class GradientBoostedTreesModel : NamedItem, IGradientBoostedTreesModel {
     // BackwardsCompatibility3.4 for allowing deserialization & serialization of old models
     #region Backwards compatible code, remove with 3.5

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

@@ -33 +33 @@
   // recalculate the actual GBT model on demand
   [Item("Gradient boosted tree model", "")]
-  public sealed class GradientBoostedTreesModelSurrogate : NamedItem, IRegressionModel {
+  public sealed class GradientBoostedTreesModelSurrogate : NamedItem, IGradientBoostedTreesModel {
     // don't store the actual model!
-    private IRegressionModel actualModel; // the actual model is only recalculated when necessary
-    public IRegressionModel Model { get { return actualModel; } }
+    private IGradientBoostedTreesModel actualModel; // the actual model is only recalculated when necessary
 
     [Storable]
@@ -87 +86 @@
 
     // wrap an actual model in a surrograte
-    public GradientBoostedTreesModelSurrogate(IRegressionProblemData trainingProblemData, uint seed, ILossFunction lossFunction, int iterations, int maxSize, double r, double m, double nu, IRegressionModel model)
+    public GradientBoostedTreesModelSurrogate(IRegressionProblemData trainingProblemData, uint seed, ILossFunction lossFunction, int iterations, int maxSize, double r, double m, double nu, IGradientBoostedTreesModel model)
       : this(trainingProblemData, seed, lossFunction, iterations, maxSize, r, m, nu) {
       this.actualModel = model;
@@ -107 +106 @@
 
 
-    private IRegressionModel RecalculateModel() {
+    private IGradientBoostedTreesModel RecalculateModel() {
       return GradientBoostedTreesAlgorithmStatic.TrainGbm(trainingProblemData, lossFunction, maxSize, nu, r, m, iterations, seed).Model;
+    }
+
+    public IEnumerable<IRegressionModel> Models {
+      get {
+        if (actualModel == null) actualModel = RecalculateModel();
+        return actualModel.Models;
+      }
+    }
+
+    public IEnumerable<double> Weights {
+      get {
+        if (actualModel == null) actualModel = RecalculateModel();
+        return actualModel.Weights;
+      }
     }
   }

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/HeuristicLab.Algorithms.DataAnalysis-3.4.csproj

@@ -201 +201 @@
     <Compile Include="GaussianProcess\GaussianProcessRegressionSolution.cs" />
     <Compile Include="GaussianProcess\ICovarianceFunction.cs" />
+    <Compile Include="GradientBoostedTrees\IGradientBoostedTreesModel.cs" />
     <Compile Include="GradientBoostedTrees\GradientBoostedTreesModelSurrogate.cs" />
     <Compile Include="GradientBoostedTrees\GradientBoostedTreesAlgorithm.cs" />
@@ -211 +212 @@
     <Compile Include="GradientBoostedTrees\LossFunctions\RelativeErrorLoss.cs" />
     <Compile Include="GradientBoostedTrees\LossFunctions\SquaredErrorLoss.cs" />
+    <Compile Include="GradientBoostedTrees\GradientBoostedTreesSolution.cs" />
     <Compile Include="GradientBoostedTrees\RegressionTreeBuilder.cs" />
     <Compile Include="GradientBoostedTrees\RegressionTreeModel.cs" />