Changeset 16842 for branches/2847_M5Regression/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/LossFunctions

Timestamp:

04/19/19 11:05:52 (5 years ago)

Author:

gkronber

Message:

#2847: merged r16565:16796 from trunk/HeuristicLab.Algorithms.DataAnalysis to branch

Location:

branches/2847_M5Regression/HeuristicLab.Algorithms.DataAnalysis

Files:

• . (modified) (1 prop)
• 3.4 (modified) (1 prop)
• 3.4/GradientBoostedTrees/LossFunctions/AbsoluteErrorLoss.cs (modified) (3 diffs)
• 3.4/GradientBoostedTrees/LossFunctions/ILossFunction.cs (modified) (2 diffs)
• 3.4/GradientBoostedTrees/LossFunctions/LogisticRegressionLoss.cs (modified) (3 diffs)
• 3.4/GradientBoostedTrees/LossFunctions/QuantileRegressionLoss.cs (modified) (3 diffs)
• 3.4/GradientBoostedTrees/LossFunctions/RelativeErrorLoss.cs (modified) (3 diffs)
• 3.4/GradientBoostedTrees/LossFunctions/SquaredErrorLoss.cs (modified) (3 diffs)

branches/2847_M5Regression/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/LossFunctions/AbsoluteErrorLoss.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  * and the BEACON Center for the Study of Evolution in Action.
  * 
@@ -25 +25 @@
 using HeuristicLab.Common;
 using HeuristicLab.Core;
-using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HEAL.Attic;
 
 namespace HeuristicLab.Algorithms.DataAnalysis {
   // loss function for the weighted absolute error
-  [StorableClass]
+  [StorableType("C4429BDA-665F-48A2-B18F-EA1569083842")]
   [Item("Absolute error loss", "")]
   public sealed class AbsoluteErrorLoss : Item, ILossFunction {
@@ -83 +83 @@
     #region item implementation
     [StorableConstructor]
-    private AbsoluteErrorLoss(bool deserializing) : base(deserializing) { }
+    private AbsoluteErrorLoss(StorableConstructorFlag _) : base(_) { }
 
     private AbsoluteErrorLoss(AbsoluteErrorLoss original, Cloner cloner) : base(original, cloner) { }

branches/2847_M5Regression/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/LossFunctions/ILossFunction.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  * and the BEACON Center for the Study of Evolution in Action.
  * 
@@ -23 +23 @@
 using System.Collections.Generic;
 using HeuristicLab.Core;
+using HEAL.Attic;
 
 namespace HeuristicLab.Algorithms.DataAnalysis {
+  [StorableType("588270d5-61ee-4906-b30f-841f64cd6724")]
   // represents an interface for loss functions used by gradient boosting
   // target represents the target vector  (original targets from the problem data, never changed)

branches/2847_M5Regression/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/LossFunctions/LogisticRegressionLoss.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  * and the BEACON Center for the Study of Evolution in Action.
  * 
@@ -26 +26 @@
 using HeuristicLab.Common;
 using HeuristicLab.Core;
-using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HEAL.Attic;
 
 namespace HeuristicLab.Algorithms.DataAnalysis {
   // Greedy Function Approximation: A Gradient Boosting Machine (page 9) 
-  [StorableClass]
+  [StorableType("E91BD71E-9A1D-4352-BD68-062290F8BE9C")]
   [Item("Logistic regression loss", "")]
   public sealed class LogisticRegressionLoss : Item, ILossFunction {
@@ -90 +90 @@
     #region item implementation
     [StorableConstructor]
-    private LogisticRegressionLoss(bool deserializing) : base(deserializing) { }
+    private LogisticRegressionLoss(StorableConstructorFlag _) : base(_) { }
 
     private LogisticRegressionLoss(LogisticRegressionLoss original, Cloner cloner) : base(original, cloner) { }

branches/2847_M5Regression/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/LossFunctions/QuantileRegressionLoss.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  * and the BEACON Center for the Study of Evolution in Action.
  * 
@@ -27 +27 @@
 using HeuristicLab.Data;
 using HeuristicLab.Parameters;
-using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HEAL.Attic;
 
 namespace HeuristicLab.Algorithms.DataAnalysis {
   // loss function for quantile regression
   // Generalized Boosted Models - A Guide To The gbm Package, Greg Ridgeway, August 2007, page 11 
-  [StorableClass]
+  [StorableType("B8EF6C18-C1A8-4B43-8FEA-A6900287ADDD")]
   [Item("QuantileRegressionloss", "Loss function for quantile regression")]
   public sealed class QuantileRegressionLoss : ParameterizedNamedItem, ILossFunction {
@@ -102 +102 @@
     #region item implementation
     [StorableConstructor]
-    private QuantileRegressionLoss(bool deserializing) : base(deserializing) { }
+    private QuantileRegressionLoss(StorableConstructorFlag _) : base(_) { }
 
     private QuantileRegressionLoss(QuantileRegressionLoss original, Cloner cloner)

branches/2847_M5Regression/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/LossFunctions/RelativeErrorLoss.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  * and the BEACON Center for the Study of Evolution in Action.
  * 
@@ -25 +25 @@
 using HeuristicLab.Common;
 using HeuristicLab.Core;
-using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HEAL.Attic;
 
 namespace HeuristicLab.Algorithms.DataAnalysis {
   // relative error loss is a special case of weighted absolute error loss with weights = (1/target)
-  [StorableClass]
+  [StorableType("1334143A-7F77-46C1-8080-0CC4F4DA8995")]
   [Item("Relative error loss", "")]
   public sealed class RelativeErrorLoss : Item, ILossFunction {
@@ -111 +111 @@
     #region item implementation
     [StorableConstructor]
-    private RelativeErrorLoss(bool deserializing) : base(deserializing) { }
+    private RelativeErrorLoss(StorableConstructorFlag _) : base(_) { }
 
     private RelativeErrorLoss(RelativeErrorLoss original, Cloner cloner) : base(original, cloner) { }

branches/2847_M5Regression/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/LossFunctions/SquaredErrorLoss.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  * and the BEACON Center for the Study of Evolution in Action.
  * 
@@ -25 +25 @@
 using HeuristicLab.Common;
 using HeuristicLab.Core;
-using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HEAL.Attic;
 
 namespace HeuristicLab.Algorithms.DataAnalysis {
-  [StorableClass]
+  [StorableType("5D02E552-B96E-4267-858B-22339D8CB6B2")]
   [Item("Squared error loss", "")]
   public sealed class SquaredErrorLoss : Item, ILossFunction {
@@ -78 +78 @@
     #region item implementation
     [StorableConstructor]
-    private SquaredErrorLoss(bool deserializing) : base(deserializing) { }
+    private SquaredErrorLoss(StorableConstructorFlag _) : base(_) { }
 
     private SquaredErrorLoss(SquaredErrorLoss original, Cloner cloner) : base(original, cloner) { }