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Ignore:
Timestamp:
01/28/19 13:41:42 (5 years ago)
Author:
gkronber
Message:

#2520: merged changes from PersistenceOverhaul branch (r16451:16564) into trunk

Location:
trunk
Files:
17 edited

Legend:

Unmodified
Added
Removed
  • trunk

  • trunk/HeuristicLab.Algorithms.DataAnalysis

  • trunk/HeuristicLab.Algorithms.DataAnalysis/3.4

  • trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesAlgorithm.cs

    r16071 r16565  
    11#region License Information
    22/* HeuristicLab
    3  * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
     3 * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
    44 * and the BEACON Center for the Study of Evolution in Action.
    55 *
     
    2929using HeuristicLab.Optimization;
    3030using HeuristicLab.Parameters;
    31 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
     31using HEAL.Attic;
    3232using HeuristicLab.PluginInfrastructure;
    3333using HeuristicLab.Problems.DataAnalysis;
     
    3535namespace HeuristicLab.Algorithms.DataAnalysis {
    3636  [Item("Gradient Boosted Trees (GBT)", "Gradient boosted trees algorithm. Specific implementation of gradient boosting for regression trees. Friedman, J. \"Greedy Function Approximation: A Gradient Boosting Machine\", IMS 1999 Reitz Lecture.")]
    37   [StorableClass]
     37  [StorableType("8CCB55BD-4935-4868-855F-D3E5D55127AA")]
    3838  [Creatable(CreatableAttribute.Categories.DataAnalysisRegression, Priority = 125)]
    3939  public class GradientBoostedTreesAlgorithm : FixedDataAnalysisAlgorithm<IRegressionProblem> {
     
    130130
    131131    [StorableConstructor]
    132     protected GradientBoostedTreesAlgorithm(bool deserializing) : base(deserializing) { }
     132    protected GradientBoostedTreesAlgorithm(StorableConstructorFlag _) : base(_) { }
    133133
    134134    protected GradientBoostedTreesAlgorithm(GradientBoostedTreesAlgorithm original, Cloner cloner)
  • trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesAlgorithmStatic.cs

    r15583 r16565  
    11#region License Information
    22/* HeuristicLab
    3  * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
     3 * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
    44 * and the BEACON Center for the Study of Evolution in Action.
    55 *
  • trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesModel.cs

    r15583 r16565  
    11#region License Information
    22/* HeuristicLab
    3  * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
     3 * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
    44 * and the BEACON Center for the Study of Evolution in Action.
    55 *
     
    2626using HeuristicLab.Common;
    2727using HeuristicLab.Core;
    28 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
     28using HEAL.Attic;
    2929using HeuristicLab.Problems.DataAnalysis;
    3030
    3131namespace HeuristicLab.Algorithms.DataAnalysis {
    32   [StorableClass]
     32  [StorableType("4EC1B359-D145-434C-A373-3EDD764D2D63")]
    3333  [Item("Gradient boosted trees model", "")]
    3434  // this is essentially a collection of weighted regression models
     
    6969
    7070    [StorableConstructor]
    71     private GradientBoostedTreesModel(bool deserializing)
    72       : base(deserializing) {
     71    private GradientBoostedTreesModel(StorableConstructorFlag _) : base(_) {
    7372      models = new List<IRegressionModel>();
    7473      weights = new List<double>();
  • trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesModelSurrogate.cs

    r15583 r16565  
    11#region License Information
    22/* HeuristicLab
    3  * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
     3 * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
    44 * and the BEACON Center for the Study of Evolution in Action.
    55 *
     
    2626using HeuristicLab.Common;
    2727using HeuristicLab.Core;
    28 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
     28using HEAL.Attic;
    2929using HeuristicLab.Problems.DataAnalysis;
    3030
    3131namespace HeuristicLab.Algorithms.DataAnalysis {
    32   [StorableClass]
     32  [StorableType("1BF7BEFB-6739-48AA-89BC-B632E72D148C")]
    3333  // this class is used as a surrogate for persistence of an actual GBT model
    3434  // since the actual GBT model would be very large when persisted we only store all necessary information to
     
    6868
    6969    [StorableConstructor]
    70     private GradientBoostedTreesModelSurrogate(bool deserializing)
    71       : base(deserializing) {
     70    private GradientBoostedTreesModelSurrogate(StorableConstructorFlag _) : base(_) {
    7271      actualModel = new Lazy<IGradientBoostedTreesModel>(() => RecalculateModel());
    7372    }
  • trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesSolution.cs

    r15583 r16565  
    11#region License Information
    22/* HeuristicLab
    3  * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
     3 * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
    44 *
    55 * This file is part of HeuristicLab.
     
    2121
    2222using HeuristicLab.Common;
    23 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
     23using HEAL.Attic;
    2424using HeuristicLab.Problems.DataAnalysis;
    2525
    2626namespace HeuristicLab.Algorithms.DataAnalysis {
    27   [StorableClass]
     27  [StorableType("B05C382A-A637-4CD6-8BCC-E1E92B60F330")]
    2828  public sealed class GradientBoostedTreesSolution : RegressionSolution {
    2929    public new IGradientBoostedTreesModel Model {
     
    3333
    3434    [StorableConstructor]
    35     private GradientBoostedTreesSolution(bool deserializing)
    36       : base(deserializing) {
     35    private GradientBoostedTreesSolution(StorableConstructorFlag _) : base(_) {
    3736    }
    3837    private GradientBoostedTreesSolution(GradientBoostedTreesSolution original, Cloner cloner)
  • trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/IGradientBoostedTreesModel.cs

    r15583 r16565  
    11#region License Information
    22/* HeuristicLab
    3  * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
     3 * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
    44 * and the BEACON Center for the Study of Evolution in Action.
    55 *
     
    2323using System.Collections.Generic;
    2424using HeuristicLab.Problems.DataAnalysis;
     25using HEAL.Attic;
    2526
    2627namespace HeuristicLab.Algorithms.DataAnalysis {
     28  [StorableType("e6c22779-7059-416d-8804-0022406b7136")]
    2729  public interface IGradientBoostedTreesModel : IRegressionModel {
    2830    IEnumerable<IRegressionModel> Models { get; }
  • trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/LossFunctions/AbsoluteErrorLoss.cs

    r15583 r16565  
    11#region License Information
    22/* HeuristicLab
    3  * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
     3 * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
    44 * and the BEACON Center for the Study of Evolution in Action.
    55 *
     
    2525using HeuristicLab.Common;
    2626using HeuristicLab.Core;
    27 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
     27using HEAL.Attic;
    2828
    2929namespace HeuristicLab.Algorithms.DataAnalysis {
    3030  // loss function for the weighted absolute error
    31   [StorableClass]
     31  [StorableType("C4429BDA-665F-48A2-B18F-EA1569083842")]
    3232  [Item("Absolute error loss", "")]
    3333  public sealed class AbsoluteErrorLoss : Item, ILossFunction {
     
    8383    #region item implementation
    8484    [StorableConstructor]
    85     private AbsoluteErrorLoss(bool deserializing) : base(deserializing) { }
     85    private AbsoluteErrorLoss(StorableConstructorFlag _) : base(_) { }
    8686
    8787    private AbsoluteErrorLoss(AbsoluteErrorLoss original, Cloner cloner) : base(original, cloner) { }
  • trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/LossFunctions/ILossFunction.cs

    r15583 r16565  
    11#region License Information
    22/* HeuristicLab
    3  * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
     3 * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
    44 * and the BEACON Center for the Study of Evolution in Action.
    55 *
     
    2323using System.Collections.Generic;
    2424using HeuristicLab.Core;
     25using HEAL.Attic;
    2526
    2627namespace HeuristicLab.Algorithms.DataAnalysis {
     28  [StorableType("588270d5-61ee-4906-b30f-841f64cd6724")]
    2729  // represents an interface for loss functions used by gradient boosting
    2830  // target represents the target vector  (original targets from the problem data, never changed)
  • trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/LossFunctions/LogisticRegressionLoss.cs

    r15583 r16565  
    11#region License Information
    22/* HeuristicLab
    3  * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
     3 * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
    44 * and the BEACON Center for the Study of Evolution in Action.
    55 *
     
    2626using HeuristicLab.Common;
    2727using HeuristicLab.Core;
    28 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
     28using HEAL.Attic;
    2929
    3030namespace HeuristicLab.Algorithms.DataAnalysis {
    3131  // Greedy Function Approximation: A Gradient Boosting Machine (page 9)
    32   [StorableClass]
     32  [StorableType("E91BD71E-9A1D-4352-BD68-062290F8BE9C")]
    3333  [Item("Logistic regression loss", "")]
    3434  public sealed class LogisticRegressionLoss : Item, ILossFunction {
     
    9090    #region item implementation
    9191    [StorableConstructor]
    92     private LogisticRegressionLoss(bool deserializing) : base(deserializing) { }
     92    private LogisticRegressionLoss(StorableConstructorFlag _) : base(_) { }
    9393
    9494    private LogisticRegressionLoss(LogisticRegressionLoss original, Cloner cloner) : base(original, cloner) { }
  • trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/LossFunctions/QuantileRegressionLoss.cs

    r15583 r16565  
    11#region License Information
    22/* HeuristicLab
    3  * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
     3 * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
    44 * and the BEACON Center for the Study of Evolution in Action.
    55 *
     
    2727using HeuristicLab.Data;
    2828using HeuristicLab.Parameters;
    29 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
     29using HEAL.Attic;
    3030
    3131namespace HeuristicLab.Algorithms.DataAnalysis {
    3232  // loss function for quantile regression
    3333  // Generalized Boosted Models - A Guide To The gbm Package, Greg Ridgeway, August 2007, page 11
    34   [StorableClass]
     34  [StorableType("B8EF6C18-C1A8-4B43-8FEA-A6900287ADDD")]
    3535  [Item("QuantileRegressionloss", "Loss function for quantile regression")]
    3636  public sealed class QuantileRegressionLoss : ParameterizedNamedItem, ILossFunction {
     
    102102    #region item implementation
    103103    [StorableConstructor]
    104     private QuantileRegressionLoss(bool deserializing) : base(deserializing) { }
     104    private QuantileRegressionLoss(StorableConstructorFlag _) : base(_) { }
    105105
    106106    private QuantileRegressionLoss(QuantileRegressionLoss original, Cloner cloner)
  • trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/LossFunctions/RelativeErrorLoss.cs

    r15583 r16565  
    11#region License Information
    22/* HeuristicLab
    3  * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
     3 * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
    44 * and the BEACON Center for the Study of Evolution in Action.
    55 *
     
    2525using HeuristicLab.Common;
    2626using HeuristicLab.Core;
    27 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
     27using HEAL.Attic;
    2828
    2929namespace HeuristicLab.Algorithms.DataAnalysis {
    3030  // relative error loss is a special case of weighted absolute error loss with weights = (1/target)
    31   [StorableClass]
     31  [StorableType("1334143A-7F77-46C1-8080-0CC4F4DA8995")]
    3232  [Item("Relative error loss", "")]
    3333  public sealed class RelativeErrorLoss : Item, ILossFunction {
     
    111111    #region item implementation
    112112    [StorableConstructor]
    113     private RelativeErrorLoss(bool deserializing) : base(deserializing) { }
     113    private RelativeErrorLoss(StorableConstructorFlag _) : base(_) { }
    114114
    115115    private RelativeErrorLoss(RelativeErrorLoss original, Cloner cloner) : base(original, cloner) { }
  • trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/LossFunctions/SquaredErrorLoss.cs

    r15583 r16565  
    11#region License Information
    22/* HeuristicLab
    3  * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
     3 * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
    44 * and the BEACON Center for the Study of Evolution in Action.
    55 *
     
    2323using System;
    2424using System.Collections.Generic;
    25 using System.Linq;
    2625using HeuristicLab.Common;
    2726using HeuristicLab.Core;
    28 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
     27using HEAL.Attic;
    2928
    3029namespace HeuristicLab.Algorithms.DataAnalysis {
    31   [StorableClass]
     30  [StorableType("5D02E552-B96E-4267-858B-22339D8CB6B2")]
    3231  [Item("Squared error loss", "")]
    3332  public sealed class SquaredErrorLoss : Item, ILossFunction {
     
    7978    #region item implementation
    8079    [StorableConstructor]
    81     private SquaredErrorLoss(bool deserializing) : base(deserializing) { }
     80    private SquaredErrorLoss(StorableConstructorFlag _) : base(_) { }
    8281
    8382    private SquaredErrorLoss(SquaredErrorLoss original, Cloner cloner) : base(original, cloner) { }
  • trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/RegressionTreeBuilder.cs

    r15583 r16565  
    11#region License Information
    22/* HeuristicLab
    3  * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
     3 * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
    44 * and the BEACON Center for the Study of Evolution in Action.
    55 *
  • trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/RegressionTreeModel.cs

    r15583 r16565  
    11#region License Information
    22/* HeuristicLab
    3  * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
     3 * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
    44 * and the BEACON Center for the Study of Evolution in Action.
    55 *
     
    2929using HeuristicLab.Core;
    3030using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
    31 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
    3231using HeuristicLab.Problems.DataAnalysis;
    3332using HeuristicLab.Problems.DataAnalysis.Symbolic;
    3433using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
     34using HEAL.Attic;
    3535
    3636namespace HeuristicLab.Algorithms.DataAnalysis {
    37   [StorableClass]
     37  [StorableType("C383410E-8707-486F-98F6-1DFB708B09B5")]
    3838  [Item("RegressionTreeModel", "Represents a decision tree for regression.")]
    3939  public sealed class RegressionTreeModel : RegressionModel {
     
    153153
    154154    [StorableConstructor]
    155     private RegressionTreeModel(bool serializing) : base(serializing) { }
     155    private RegressionTreeModel(StorableConstructorFlag _) : base(_) { }
    156156    // cloning ctor
    157157    private RegressionTreeModel(RegressionTreeModel original, Cloner cloner)
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