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Timestamp:
04/14/17 08:58:45 (7 years ago)
Author:
gkronber
Message:

#2699: merged changesets from trunk to branch

Location:
branches/RBFRegression/HeuristicLab.Algorithms.DataAnalysis/3.4
Files:
2 edited

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  • branches/RBFRegression/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/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/histogram/HeuristicLab.Algorithms.DataAnalysis/3.45959-6341
  • branches/RBFRegression/HeuristicLab.Algorithms.DataAnalysis/3.4/TimeSeries/AutoregressiveModeling.cs

    r14185 r14869  
    2222using System;
    2323using System.Linq;
     24using System.Threading;
    2425using HeuristicLab.Common;
    2526using HeuristicLab.Core;
     
    6364    }
    6465
    65     protected override void Run() {
     66    protected override void Run(CancellationToken cancellationToken) {
    6667      double rmsError, cvRmsError;
    6768      var solution = CreateAutoRegressiveSolution(Problem.ProblemData, TimeOffset, out rmsError, out cvRmsError);
     
    114115      alglib.lrunpack(lm, out coefficients, out nFeatures);
    115116
    116 
    117       ISymbolicExpressionTree tree = new SymbolicExpressionTree(new ProgramRootSymbol().CreateTreeNode());
    118       ISymbolicExpressionTreeNode startNode = new StartSymbol().CreateTreeNode();
    119       tree.Root.AddSubtree(startNode);
    120       ISymbolicExpressionTreeNode addition = new Addition().CreateTreeNode();
    121       startNode.AddSubtree(addition);
    122 
    123       for (int i = 0; i < timeOffset; i++) {
    124         LaggedVariableTreeNode node = (LaggedVariableTreeNode)new LaggedVariable().CreateTreeNode();
    125         node.VariableName = targetVariable;
    126         node.Weight = coefficients[i];
    127         node.Lag = (i + 1) * -1;
    128         addition.AddSubtree(node);
    129       }
    130 
    131       ConstantTreeNode cNode = (ConstantTreeNode)new Constant().CreateTreeNode();
    132       cNode.Value = coefficients[coefficients.Length - 1];
    133       addition.AddSubtree(cNode);
     117      var tree = LinearModelToTreeConverter.CreateTree(
     118        variableNames: Enumerable.Repeat(problemData.TargetVariable, nFeatures).ToArray(),
     119        lags: Enumerable.Range(0, timeOffset).Select(i => (i + 1) * -1).ToArray(),
     120        coefficients: coefficients.Take(nFeatures).ToArray(),
     121        @const: coefficients[nFeatures]
     122        );
    134123
    135124      var interpreter = new SymbolicTimeSeriesPrognosisExpressionTreeInterpreter(problemData.TargetVariable);
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