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Timestamp:
08/10/12 20:42:30 (12 years ago)
Author:
gkronber
Message:

#1902 worked on GPR: added line chart, made parameters of mean and covariance functions readable, removed target variable scaling, moved noise hyperparameter for likelihood function to the end of the parameter list, added methods to calculate the predicted variance, removed limits for scale of covariance functions and introduced exception handling to catch non-spd or singular cov matrixes, implemented rational quadratic covariance function, added unit test case from GBML book (however it does not work as the book seemingly uses a noise-less likelihood function)

File:
1 edited

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  • trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/CovarianceSEiso.cs

    r8463 r8473  
    3737    [Storable]
    3838    private double sf2;
     39    public double Scale { get { return sf2; } }
    3940    [Storable]
    4041    private double l;
     42    public double Length { get { return l; } }
    4143    [Storable]
    4244    private bool symmetric;
     
    8082    public void SetParameter(double[] hyp) {
    8183      this.l = Math.Exp(hyp[0]);
    82       this.sf2 = Math.Min(1E6, Math.Exp(2 * hyp[1])); // upper limit for scale
     84      this.sf2 = Math.Exp(2 * hyp[1]);
    8385      sd = null;
    8486    }
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