Changeset 15160


Ignore:
Timestamp:
07/06/17 14:07:38 (3 months ago)
Author:
gkronber
Message:

#2782 renamed LOO log predictive probability to LooCvNegativeLogPseudoLikelihood

Location:
trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4
Files:
4 edited

Legend:

Unmodified
Added
Removed
  • trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/GaussianProcessModel.cs

    r14918 r15160  
    4646
    4747    [Storable]
    48     private double negativeLooPredictiveProbability;
    49     public double NegativeLooPredictiveProbability {
    50       get { return negativeLooPredictiveProbability; }
     48    private double loocvNegLogPseudoLikelihood;
     49    public double LooCvNegativeLogPseudoLikelihood {
     50      get { return loocvNegLogPseudoLikelihood; }
    5151    }
    5252
     
    134134      this.trainingDataset = cloner.Clone(original.trainingDataset);
    135135      this.negativeLogLikelihood = original.negativeLogLikelihood;
    136       this.negativeLooPredictiveProbability = original.negativeLooPredictiveProbability;
     136      this.loocvNegLogPseudoLikelihood = original.loocvNegLogPseudoLikelihood;
    137137      this.sqrSigmaNoise = original.sqrSigmaNoise;
    138138      if (original.meanParameter != null) {
     
    225225      if (info != 1) throw new ArgumentException("Can't invert matrix to calculate gradients.");
    226226
    227       // LOOCV log predictive probability (GPML page 116 and 117)
     227      // LOOCV log pseudo-likelihood (or log predictive probability) (GPML page 116 and 117)
    228228      var sumLoo = 0.0;
    229229      var ki = new double[n];
     
    238238      }
    239239      sumLoo += n * Math.Log(2 * Math.PI);
    240       negativeLooPredictiveProbability = 0.5 * sumLoo;
     240      loocvNegLogPseudoLikelihood = 0.5 * sumLoo;
    241241
    242242      for (int i = 0; i < n; i++) {
  • trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/GaussianProcessRegressionModelCreator.cs

    r14899 r15160  
    6565        ModelParameter.ActualValue = model;
    6666        NegativeLogLikelihoodParameter.ActualValue = new DoubleValue(model.NegativeLogLikelihood);
    67         NegativeLogPredictiveProbabilityParameter.ActualValue = new DoubleValue(model.NegativeLooPredictiveProbability);
     67        NegativeLogPredictiveProbabilityParameter.ActualValue = new DoubleValue(model.LooCvNegativeLogPseudoLikelihood);
    6868        HyperparameterGradientsParameter.ActualValue = new RealVector(model.HyperparameterGradients);
    6969        return base.Apply();
  • trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/GaussianProcessRegressionSolutionCreator.cs

    r14899 r15160  
    4141    private const string TestRSquaredResultName = "Test R²";
    4242    private const string CreateSolutionParameterName = "CreateSolution";
    43     private const string NegLogPredictiveProbability = "NegativeLogPredictiveProbability (LOO-CV)";
     43    private const string NegLogPseudoLikelihood = "Negative log pseudo-likelihood (LOO-CV)";
    4444
    4545    #region Parameter Properties
     
    109109                                 "The Pearson's R² of the Gaussian process solution on the test partition.",
    110110                                 new DoubleValue(s.TestRSquared)));
    111           results.Add(new Result(NegLogPredictiveProbability,
    112                                  "The leave-one-out-cross-validation negative log predictive probability.",
    113                                  new DoubleValue(m.NegativeLooPredictiveProbability)));
     111          results.Add(new Result(NegLogPseudoLikelihood,
     112                                 "The negative log pseudo-likelihood (from leave-one-out-cross-validation).",
     113                                 new DoubleValue(m.LooCvNegativeLogPseudoLikelihood)));
    114114        } else {
    115115          results[SolutionParameterName].Value = s;
    116116          results[TrainingRSquaredResultName].Value = new DoubleValue(s.TrainingRSquared);
    117117          results[TestRSquaredResultName].Value = new DoubleValue(s.TestRSquared);
    118           results[NegLogPredictiveProbability].Value = new DoubleValue(m.NegativeLooPredictiveProbability);
     118          results[NegLogPseudoLikelihood].Value = new DoubleValue(m.LooCvNegativeLogPseudoLikelihood);
    119119        }
    120120      }
  • trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/Interfaces/IGaussianProcessModel.cs

    r14899 r15160  
    2828  public interface IGaussianProcessModel : IConfidenceRegressionModel {
    2929    double NegativeLogLikelihood { get; }
    30     double NegativeLooPredictiveProbability { get; }
     30    double LooCvNegativeLogPseudoLikelihood { get; }
    3131    double SigmaNoise { get; }
    3232    IMeanFunction MeanFunction { get; }
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