Changeset 2130 for trunk/sources/HeuristicLab.GP.StructureIdentification

Timestamp:

07/02/09 13:17:14 (16 years ago)

Author:

gkronber

Message:

• Removed "AutoRegressive" parameter for GP completely. User is responsible to set allowed features correctly (including the target variable for auto regression)
• Setting allowed features correctly in the CEDMA dispatcher (this fixes the problem of incorrect input variables in SVM)

#683 (nu-SVR engine doesn't filter allowed features to remove the target variable)

Location:

trunk/sources/HeuristicLab.GP.StructureIdentification

Files:

• 3.3/Evaluators/GPEvaluatorBase.cs (modified) (1 diff)
• 3.3/FunctionLibraryInjector.cs (modified) (3 diffs)
• 3.3/OffspringSelectionGP.cs (modified) (1 diff)
• 3.3/StandardGP.cs (modified) (1 diff)
• 3.4/Evaluators/GPEvaluatorBase.cs (modified) (1 diff)

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

@@ -44 +44 @@
       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));
-      AddVariableInfo(new VariableInfo("UseEstimatedTargetValue", "Wether to use the original (measured) or the estimated (calculated) value for the targat variable when doing autoregressive modelling", typeof(BoolData), VariableKind.In));
+      AddVariableInfo(new VariableInfo("UseEstimatedTargetValue", "Wether to use the original (measured) or the estimated (calculated) value for the target variable for autoregressive modelling", typeof(BoolData), VariableKind.In));
     }
 

trunk/sources/HeuristicLab.GP.StructureIdentification/3.3/FunctionLibraryInjector.cs ¶

@@ -35 +35 @@
     private const string TARGETVARIABLE = "TargetVariable";
     private const string ALLOWEDFEATURES = "AllowedFeatures";
-    private const string AUTOREGRESSIVE = "Autoregressive";
     private const string MINTIMEOFFSET = "MinTimeOffset";
     private const string MAXTIMEOFFSET = "MaxTimeOffset";
@@ -73 +72 @@
       AddVariableInfo(new VariableInfo(TARGETVARIABLE, "The target variable", typeof(IntData), VariableKind.In));
       AddVariableInfo(new VariableInfo(ALLOWEDFEATURES, "List of indexes of allowed features", typeof(ItemList<IntData>), VariableKind.In));
-      AddVariableInfo(new Core.VariableInfo(AUTOREGRESSIVE, "Switch to turn on/off autoregressive modeling (wether to allow the target variable as input)", typeof(BoolData), Core.VariableKind.In));
       AddVariableInfo(new Core.VariableInfo(MINTIMEOFFSET, "Minimal time offset for all features", typeof(IntData), Core.VariableKind.In));
       AddVariableInfo(new Core.VariableInfo(MAXTIMEOFFSET, "Maximal time offset for all feature", typeof(IntData), Core.VariableKind.In));
@@ -123 +121 @@
       IItem maxTimeOffsetItem = GetVariableValue(MAXTIMEOFFSET, scope, true, false);
       int maxTimeOffset = maxTimeOffsetItem == null ? 0 : ((IntData)maxTimeOffsetItem).Data;
-      // try to get flag autoregressive (use false as default if not available)
-      IItem autoRegItem = GetVariableValue(AUTOREGRESSIVE, scope, true, false);
-      bool autoregressive = autoRegItem == null ? false : ((BoolData)autoRegItem).Data;
-
-      if (autoregressive) {
-        // make sure the target-variable occures in list of allowed features
-        if (!allowedFeatures.Exists(d => d.Data == targetVariable)) allowedFeatures.Add(new IntData(targetVariable));
-      } else {
-        // remove the target-variable in case it occures in allowed features
-        List<IntData> ts = allowedFeatures.FindAll(d => d.Data == targetVariable);
-        foreach (IntData t in ts) allowedFeatures.Remove(t);
-      }
 
       variable = new StructId.Variable();

trunk/sources/HeuristicLab.GP.StructureIdentification/3.3/OffspringSelectionGP.cs ¶

@@ -75 +75 @@
       PopulationSize = 1000;
       Parents = 20;
-      MaxEvaluatedSolutions = 1000000;
-      SelectionPressureLimit = 300;
+      MaxEvaluatedSolutions = 5000000;
+      SelectionPressureLimit = 400;
       ComparisonFactor = 1.0;
       SuccessRatioLimit = 1.0;

trunk/sources/HeuristicLab.GP.StructureIdentification/3.3/StandardGP.cs ¶

@@ -99 +99 @@
       : base() {
       PopulationSize = 10000;
-      MaxGenerations = 100;
+      MaxGenerations = 500;
       TournamentSize = 7;
       MutationRate = 0.15;

trunk/sources/HeuristicLab.GP.StructureIdentification/3.4/Evaluators/GPEvaluatorBase.cs ¶

@@ -42 +42 @@
       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));
-      AddVariableInfo(new VariableInfo("UseEstimatedTargetValue", "Wether to use the original (measured) or the estimated (calculated) value for the targat variable when doing autoregressive modelling", typeof(BoolData), VariableKind.In));
+      AddVariableInfo(new VariableInfo("UseEstimatedTargetValue", "Wether to use the original (measured) or the estimated (calculated) value for the target variable for autoregressive modelling", typeof(BoolData), VariableKind.In));
     }