Changeset 15187 for trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess

Timestamp:

07/10/17 19:16:40 (7 years ago)

Author:

gkronber

Message:

#2782: renamed remaining fields and properties referring to 'PredictiveProbability'

Location:

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess

Files:

• GaussianProcessModelCreator.cs (modified) (4 diffs)
• GaussianProcessRegressionModelCreator.cs (modified) (1 diff)

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/GaussianProcessModelCreator.cs

@@ -37 +37 @@
     private const string ModelParameterName = "Model";
     private const string NegativeLogLikelihoodParameterName = "NegativeLogLikelihood";
-    private const string NegativeLogPredictiveProbabilityParameterName = "NegativeLogPredictiveProbability (LOOCV)";
+    private const string NegativeLogPseudoLikelihoodParameterName = "NegativeLogPseudoLikelihood (LOOCV)";
     private const string HyperparameterGradientsParameterName = "HyperparameterGradients";
     protected const string ScaleInputValuesParameterName = "ScaleInputValues";
@@ -62 +62 @@
       get { return (ILookupParameter<DoubleValue>)Parameters[NegativeLogLikelihoodParameterName]; }
     }
-    public ILookupParameter<DoubleValue> NegativeLogPredictiveProbabilityParameter {
-      get { return (ILookupParameter<DoubleValue>)Parameters[NegativeLogPredictiveProbabilityParameterName]; }
+    public ILookupParameter<DoubleValue> NegativeLogPseudoLikelihoodParameter {
+      get { return (ILookupParameter<DoubleValue>)Parameters[NegativeLogPseudoLikelihoodParameterName]; }
     }
     public ILookupParameter<BoolValue> ScaleInputValuesParameter {
@@ -90 +90 @@
       Parameters.Add(new LookupParameter<RealVector>(HyperparameterGradientsParameterName, "The gradients of the hyperparameters for the produced Gaussian process model (necessary for hyperparameter optimization)"));
       Parameters.Add(new LookupParameter<DoubleValue>(NegativeLogLikelihoodParameterName, "The negative log-likelihood of the produced Gaussian process model given the data."));
-      Parameters.Add(new LookupParameter<DoubleValue>(NegativeLogPredictiveProbabilityParameterName, "The leave-one-out-cross-validation negative log predictive probability of the produced Gaussian process model given the data."));
+      Parameters.Add(new LookupParameter<DoubleValue>(NegativeLogPseudoLikelihoodParameterName, "The leave-one-out-cross-validation negative log pseudo-likelihood of the produced Gaussian process model given the data."));
 
 
@@ -105 +105 @@
         Parameters[ScaleInputValuesParameterName].Hidden = true;
       }
-      if (!Parameters.ContainsKey(NegativeLogPredictiveProbabilityParameterName)) {
-        Parameters.Add(new LookupParameter<DoubleValue>(NegativeLogPredictiveProbabilityParameterName,
-          "The leave-one-out-cross-validation negative log predictive probability of the produced Gaussian process model given the data."));
+      if (!Parameters.ContainsKey(NegativeLogPseudoLikelihoodParameterName)) {
+        Parameters.Add(new LookupParameter<DoubleValue>(NegativeLogPseudoLikelihoodParameterName,
+          "The leave-one-out-cross-validation negative log pseudo-likelihood of the produced Gaussian process model given the data."));
       }
     }

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/GaussianProcessRegressionModelCreator.cs

@@ -65 +65 @@
         ModelParameter.ActualValue = model;
         NegativeLogLikelihoodParameter.ActualValue = new DoubleValue(model.NegativeLogLikelihood);
-        NegativeLogPredictiveProbabilityParameter.ActualValue = new DoubleValue(model.LooCvNegativeLogPseudoLikelihood);
+        NegativeLogPseudoLikelihoodParameter.ActualValue = new DoubleValue(model.LooCvNegativeLogPseudoLikelihood);
         HyperparameterGradientsParameter.ActualValue = new RealVector(model.HyperparameterGradients);
         return base.Apply();