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Ignore:
Timestamp:
01/31/17 13:01:08 (8 years ago)
Author:
gkronber
Message:

#2660: removed obsolete comment

File:
1 edited

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  • trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/VariableNetworks/VariableNetwork.cs

    r14291 r14623  
    218218      relevance = CalculateRelevance(y, u, xs, l);
    219219
    220 
    221       // calculate variable relevance
    222       // as per Rasmussen and Williams "Gaussian Processes for Machine Learning" page 106:
    223       // ,,For the squared exponential covariance function [...] the l1, ..., lD hyperparameters
    224       // play the role of characteristic length scales [...]. Such a covariance function implements
    225       // automatic relevance determination (ARD) [Neal, 1996], since the inverse of the length-scale
    226       // determines how relevant an input is: if the length-scale has a very large value, the covariance
    227       // will become almost independent of that input, effectively removing it from inference.''
    228       // relevance = l.Select(li => 1.0 / li).ToArray();
    229 
    230220      return y;
    231221    }
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