Changeset 13184 for stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesModelSurrogate.cs

Timestamp:

11/16/15 19:49:40 (8 years ago)

Author:

gkronber

Message:

#2450: merged r12868,r12873,r12875,r13065:13066,r13157:13158 from trunk to stable

Location:

stable

Files:

• . (modified) (1 prop)
• HeuristicLab.Algorithms.DataAnalysis (modified) (1 prop)
• HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesModelSurrogate.cs (copied) (copied from trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesModelSurrogate.cs) (7 diffs)

stable/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesModelSurrogate.cs

@@ -21 +21 @@
 #endregion
 
-using System;
 using System.Collections.Generic;
-using System.Linq;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
-using HeuristicLab.PluginInfrastructure;
 using HeuristicLab.Problems.DataAnalysis;
 
@@ -36 +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
+    private IGradientBoostedTreesModel actualModel; // the actual model is only recalculated when necessary
 
     [Storable]
@@ -45 +42 @@
     private readonly uint seed;
     [Storable]
-    private string lossFunctionName;
+    private ILossFunction lossFunction;
     [Storable]
     private double r;
@@ -66 +63 @@
 
       this.trainingProblemData = cloner.Clone(original.trainingProblemData);
+      this.lossFunction = cloner.Clone(original.lossFunction);
       this.seed = original.seed;
-      this.lossFunctionName = original.lossFunctionName;
       this.iterations = original.iterations;
       this.maxSize = original.maxSize;
@@ -76 +73 @@
 
     // create only the surrogate model without an actual model
-    public GradientBoostedTreesModelSurrogate(IRegressionProblemData trainingProblemData, uint seed, string lossFunctionName, int iterations, int maxSize, double r, double m, double nu)
+    public GradientBoostedTreesModelSurrogate(IRegressionProblemData trainingProblemData, uint seed, ILossFunction lossFunction, int iterations, int maxSize, double r, double m, double nu)
       : base("Gradient boosted tree model", string.Empty) {
       this.trainingProblemData = trainingProblemData;
       this.seed = seed;
-      this.lossFunctionName = lossFunctionName;
+      this.lossFunction = lossFunction;
       this.iterations = iterations;
       this.maxSize = maxSize;
@@ -89 +86 @@
 
     // wrap an actual model in a surrograte
-    public GradientBoostedTreesModelSurrogate(IRegressionProblemData trainingProblemData, uint seed, string lossFunctionName, int iterations, int maxSize, double r, double m, double nu, IRegressionModel model)
-      : this(trainingProblemData, seed, lossFunctionName, iterations, maxSize, r, m, nu) {
+    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;
     }
@@ -109 +106 @@
 
 
-    private IRegressionModel RecalculateModel() {
-      var lossFunction = ApplicationManager.Manager.GetInstances<ILossFunction>().Single(l => l.ToString() == lossFunctionName);
+    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;
+      }
     }
   }