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Timestamp:
01/15/18 08:21:48 (6 years ago)
Author:
bwerth
Message:

#2847 made changes to M5 according to review comments

Location:
branches/M5Regression/HeuristicLab.Algorithms.DataAnalysis
Files:
3 edited

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  • branches/M5Regression/HeuristicLab.Algorithms.DataAnalysis

  • branches/M5Regression/HeuristicLab.Algorithms.DataAnalysis/3.4

    • Property svn:mergeinfo set to (toggle deleted branches)
      /stable/HeuristicLab.Algorithms.DataAnalysis/3.4mergedeligible
      /trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4mergedeligible
      /branches/1721-RandomForestPersistence/HeuristicLab.Algorithms.DataAnalysis/3.410321-10322
      /branches/Async/HeuristicLab.Algorithms.DataAnalysis/3.413329-15286
      /branches/Benchmarking/sources/HeuristicLab.Algorithms.DataAnalysis/3.46917-7005
      /branches/ClassificationModelComparison/HeuristicLab.Algorithms.DataAnalysis/3.49070-13099
      /branches/CloningRefactoring/HeuristicLab.Algorithms.DataAnalysis/3.44656-4721
      /branches/DataAnalysis Refactoring/HeuristicLab.Algorithms.DataAnalysis/3.45471-5808
      /branches/DataAnalysis SolutionEnsembles/HeuristicLab.Algorithms.DataAnalysis/3.45815-6180
      /branches/DataAnalysis/HeuristicLab.Algorithms.DataAnalysis/3.44458-4459,​4462,​4464
      /branches/DataPreprocessing/HeuristicLab.Algorithms.DataAnalysis/3.410085-11101
      /branches/GP.Grammar.Editor/HeuristicLab.Algorithms.DataAnalysis/3.46284-6795
      /branches/GP.Symbols (TimeLag, Diff, Integral)/HeuristicLab.Algorithms.DataAnalysis/3.45060
      /branches/HeuristicLab.DatasetRefactor/sources/HeuristicLab.Algorithms.DataAnalysis/3.411570-12508
      /branches/HeuristicLab.Problems.Orienteering/HeuristicLab.Algorithms.DataAnalysis/3.411130-12721
      /branches/HeuristicLab.RegressionSolutionGradientView/HeuristicLab.Algorithms.DataAnalysis/3.413819-14091
      /branches/HeuristicLab.TimeSeries/HeuristicLab.Algorithms.DataAnalysis/3.48116-8789
      /branches/LogResidualEvaluator/HeuristicLab.Algorithms.DataAnalysis/3.410202-10483
      /branches/NET40/sources/HeuristicLab.Algorithms.DataAnalysis/3.45138-5162
      /branches/ParallelEngine/HeuristicLab.Algorithms.DataAnalysis/3.45175-5192
      /branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Algorithms.DataAnalysis/3.47773-7810
      /branches/QAPAlgorithms/HeuristicLab.Algorithms.DataAnalysis/3.46350-6627
      /branches/Restructure trunk solution/HeuristicLab.Algorithms.DataAnalysis/3.46828
      /branches/SpectralKernelForGaussianProcesses/HeuristicLab.Algorithms.DataAnalysis/3.410204-10479
      /branches/SuccessProgressAnalysis/HeuristicLab.Algorithms.DataAnalysis/3.45370-5682
      /branches/Trunk/HeuristicLab.Algorithms.DataAnalysis/3.46829-6865
      /branches/VNS/HeuristicLab.Algorithms.DataAnalysis/3.45594-5752
      /branches/Weighted TSNE/3.415451-15531
      /branches/histogram/HeuristicLab.Algorithms.DataAnalysis/3.45959-6341
      /branches/symbreg-factors-2650/HeuristicLab.Algorithms.DataAnalysis/3.414232-14825
  • branches/M5Regression/HeuristicLab.Algorithms.DataAnalysis/3.4/M5Regression/LeafTypes/ConstantLeaf.cs

    r15430 r15614  
    3131  [StorableClass]
    3232  [Item("ConstantLeaf", "A leaf type that uses constant models as leaf models")]
    33   public class ConstantLeaf : ParameterizedNamedItem, ILeafType<IRegressionModel> {
     33  public class ConstantLeaf : ParameterizedNamedItem, ILeafModel {
    3434    #region Constructors & Cloning
    3535    [StorableConstructor]
     
    4343
    4444    #region IModelType
    45     public IRegressionModel BuildModel(IRegressionProblemData pd, IRandom random, CancellationToken cancellation, out int noParameters) {
     45    public bool ProvidesConfidence {
     46      get { return false; }
     47    }
     48    public IRegressionModel Build(IRegressionProblemData pd, IRandom random, CancellationToken cancellationToken, out int noParameters) {
    4649      if (pd.Dataset.Rows < MinLeafSize(pd)) throw new ArgumentException("The number of training instances is too small to create a linear model");
    4750      noParameters = 1;
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