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Timestamp:
08/27/14 10:29:38 (10 years ago)
Author:
mkommend
Message:

#2175: Merged trunk changes into complexity branch.

Location:
branches/DataAnalysis.ComplexityAnalyzer/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression
Files:
3 edited

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  • branches/DataAnalysis.ComplexityAnalyzer/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression

  • branches/DataAnalysis.ComplexityAnalyzer/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4

    • Property svn:mergeinfo set to (toggle deleted branches)
      /branches/HLScript/HeuristicLab.Problems.DataAnalysis.Symbolic.Regressionmergedeligible
      /stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Regressionmergedeligible
      /trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4mergedeligible
      /branches/Benchmarking/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression6917-7005
      /branches/CloningRefactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression4656-4721
      /branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression5471-5473
      /branches/DataAnalysis SolutionEnsembles/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression5815-6180
      /branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression4458-4459,​4462,​4464
      /branches/DataPreprocessing/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression10085-11101
      /branches/GP.Grammar.Editor/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression6284-6795
      /branches/GP.Symbols (TimeLag, Diff, Integral)/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression5060
      /branches/HeuristicLab.TreeSimplifier/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression8388-8942
      /branches/LogResidualEvaluator/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression10202-10483
      /branches/NET40/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression5138-5162
      /branches/ParallelEngine/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression5175-5192
      /branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression7748-7810
      /branches/QAPAlgorithms/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression6350-6627
      /branches/Restructure trunk solution/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression6828
      /branches/SpectralKernelForGaussianProcesses/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression10204-10479
      /branches/SuccessProgressAnalysis/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression5370-5682
      /branches/Trunk/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression6829-6865
      /branches/VNS/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression5594-5752
      /branches/histogram/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression5959-6341
  • branches/DataAnalysis.ComplexityAnalyzer/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SymbolicRegressionPruningOperator.cs

    r10469 r11310  
    1 using System.Linq;
     1#region License Information
     2
     3/* HeuristicLab
     4 * Copyright (C) 2002-2014 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
     5 *
     6 * This file is part of HeuristicLab.
     7 *
     8 * HeuristicLab is free software: you can redistribute it and/or modify
     9 * it under the terms of the GNU General Public License as published by
     10 * the Free Software Foundation, either version 3 of the License, or
     11 * (at your option) any later version.
     12 *
     13 * HeuristicLab is distributed in the hope that it will be useful,
     14 * but WITHOUT ANY WARRANTY; without even the implied warranty of
     15 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
     16 * GNU General Public License for more details.
     17 *
     18 * You should have received a copy of the GNU General Public License
     19 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
     20 */
     21
     22#endregion
     23
     24using System.Linq;
    225using HeuristicLab.Common;
    326using HeuristicLab.Core;
     
    1033  public class SymbolicRegressionPruningOperator : SymbolicDataAnalysisExpressionPruningOperator {
    1134    private const string ImpactValuesCalculatorParameterName = "ImpactValuesCalculator";
    12     private const string ImpactValuesCalculatorParameterDescription = "The impact values calculator to be used for figuring out the node impacts.";
    13 
    14     private const string EvaluatorParameterName = "Evaluator";
    15 
    16     public ILookupParameter<ISymbolicRegressionSingleObjectiveEvaluator> EvaluatorParameter {
    17       get { return (ILookupParameter<ISymbolicRegressionSingleObjectiveEvaluator>)Parameters[EvaluatorParameterName]; }
    18     }
    1935
    2036    protected SymbolicRegressionPruningOperator(SymbolicRegressionPruningOperator original, Cloner cloner)
     
    3046    public SymbolicRegressionPruningOperator() {
    3147      var impactValuesCalculator = new SymbolicRegressionSolutionImpactValuesCalculator();
    32       Parameters.Add(new ValueParameter<ISymbolicDataAnalysisSolutionImpactValuesCalculator>(ImpactValuesCalculatorParameterName, ImpactValuesCalculatorParameterDescription, impactValuesCalculator));
    33       Parameters.Add(new LookupParameter<ISymbolicRegressionSingleObjectiveEvaluator>(EvaluatorParameterName));
     48      Parameters.Add(new ValueParameter<ISymbolicDataAnalysisSolutionImpactValuesCalculator>(ImpactValuesCalculatorParameterName, "The impact values calculator to be used for figuring out the node impacts.", impactValuesCalculator));
    3449    }
    3550
     
    4156      var regressionModel = (IRegressionModel)model;
    4257      var regressionProblemData = (IRegressionProblemData)ProblemData;
    43       var trainingIndices = ProblemData.TrainingIndices.ToList();
     58      var trainingIndices = Enumerable.Range(FitnessCalculationPartition.Start, FitnessCalculationPartition.Size);
    4459      var estimatedValues = regressionModel.GetEstimatedValues(ProblemData.Dataset, trainingIndices); // also bounds the values
    4560      var targetValues = ProblemData.Dataset.GetDoubleValues(regressionProblemData.TargetVariable, trainingIndices);
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