Changeset 2328 for trunk/sources/HeuristicLab.GP.StructureIdentification/3.3/Evaluators

Timestamp:

09/03/09 15:00:23 (15 years ago)

Author:

gkronber

Message:

this is the remaining part of changeset r2327.
Applied changes in modeling plugins that are necessary for the new model analyzer (#722)

• predictor has properties for the lower and upper limit of the predicted value
• added views for predictors that show the limits (also added a new view for GeneticProgrammingModel that shows the size and height of the model)
• Reintroduced TreeEvaluatorInjectors that read a PunishmentFactor and calculate the lower and upper limits for estimated values (limits are set in the tree evaluators)
• Added operators to create Predictors. Changed modeling algorithms to use the predictors for the calculation of final model qualities and variable impacts (to be compatible with the new model analyzer the predictors use a very large PunishmentFactor)
• replaced all private implementations of double.IsAlmost and use HL.Commons instead (see #733 r2324)
• Implemented operator SolutionExtractor and moved BestSolutionStorer from HL.Logging to HL.Modeling (fixes #734)

File:

• trunk/sources/HeuristicLab.GP.StructureIdentification/3.3/Evaluators/GPEvaluatorBase.cs (modified) (2 diffs)

trunk/sources/HeuristicLab.GP.StructureIdentification/3.3/Evaluators/GPEvaluatorBase.cs

@@ -34 +34 @@
       AddVariableInfo(new VariableInfo("TargetVariable", "Index of the column of the dataset that holds the target variable", typeof(IntData), VariableKind.In));
       AddVariableInfo(new VariableInfo("TotalEvaluatedNodes", "Number of evaluated nodes", typeof(DoubleData), VariableKind.In | VariableKind.Out));
-      AddVariableInfo(new VariableInfo("TrainingSamplesStart", "Start index of training samples in dataset", typeof(IntData), VariableKind.In));
-      AddVariableInfo(new VariableInfo("TrainingSamplesEnd", "End index of training samples in dataset", typeof(IntData), VariableKind.In));
       AddVariableInfo(new VariableInfo("SamplesStart", "Start index of samples in dataset to evaluate", typeof(IntData), VariableKind.In));
       AddVariableInfo(new VariableInfo("SamplesEnd", "End index of samples in dataset to evaluate", typeof(IntData), VariableKind.In));
@@ -47 +45 @@
       IGeneticProgrammingModel gpModel = GetVariableValue<IGeneticProgrammingModel>("FunctionTree", scope, true);
       double totalEvaluatedNodes = scope.GetVariableValue<DoubleData>("TotalEvaluatedNodes", true).Data;
-      int trainingStart = GetVariableValue<IntData>("TrainingSamplesStart", scope, true).Data;
-      int trainingEnd = GetVariableValue<IntData>("TrainingSamplesEnd", scope, true).Data;
       int start = GetVariableValue<IntData>("SamplesStart", scope, true).Data;
       int end = GetVariableValue<IntData>("SamplesEnd", scope, true).Data;
       bool useEstimatedValues = GetVariableValue<BoolData>("UseEstimatedTargetValue", scope, true).Data;
       ITreeEvaluator evaluator = GetVariableValue<ITreeEvaluator>("TreeEvaluator", scope, true);
-      evaluator.PrepareForEvaluation(dataset, targetVariable, trainingStart, trainingEnd, gpModel.FunctionTree);
+      evaluator.PrepareForEvaluation(dataset, gpModel.FunctionTree);
 
       double[] backupValues = null;