Changeset 12869

Timestamp:

08/17/15 16:35:47 (9 years ago)

Author:

gkronber

Message:

#2434: merged r12835:12868 from trunk to cross-validation branch

Location:

branches/crossvalidation-2434

Files:

• . (modified) (1 prop)
• HeuristicLab 3.3.sln (modified) (3 diffs)
• HeuristicLab.Algorithms.DataAnalysis (modified) (1 prop)
• HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesAlgorithm.cs (modified) (2 diffs)
• HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesModel.cs (modified) (2 diffs)
• HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesModelSurrogate.cs (copied) (copied from trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesModelSurrogate.cs)
• HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/RegressionTreeModel.cs (modified) (1 diff)
• HeuristicLab.Algorithms.DataAnalysis/3.4/HeuristicLab.Algorithms.DataAnalysis-3.4.csproj (modified) (1 diff)
• HeuristicLab.Analysis.Statistics.Views/3.3/StatisticalTestsView.cs (modified) (4 diffs)
• HeuristicLab.Encodings.IntegerVectorEncoding (modified) (1 prop)
• HeuristicLab.Encodings.IntegerVectorEncoding/3.3/IntegerVectorEncoding.cs (modified) (1 diff)
• HeuristicLab.Encodings.RealVectorEncoding (modified) (1 prop)
• HeuristicLab.Encodings.RealVectorEncoding/3.3/RealVectorEncoding.cs (modified) (1 diff)
• HeuristicLab.Encodings.SymbolicExpressionTreeEncoding (modified) (1 prop)
• HeuristicLab.Encodings.SymbolicExpressionTreeEncoding/3.4/Creators/FullTreeCreator.cs (modified) (3 diffs)
• HeuristicLab.Encodings.SymbolicExpressionTreeEncoding/3.4/Creators/GrowTreeCreator.cs (modified) (1 diff)
• HeuristicLab.ParallelEngine.Views/3.3/HeuristicLab.ParallelEngine.Views-3.3.csproj (copied) (copied from trunk/sources/HeuristicLab.ParallelEngine.Views/3.3/HeuristicLab.ParallelEngine.Views-3.3.csproj)
• HeuristicLab.ParallelEngine.Views/3.3/HeuristicLab.ParallelEngine.Views.csproj (deleted)
• HeuristicLab.Problems.DataAnalysis (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/TreeMatching/SymbolicExpressionTreePhenotypicSimilarityCalculator.cs (modified) (2 diffs)
• HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/Regression/IRegressionSolution.cs (modified) (1 diff)
• HeuristicLab.Problems.LawnMower (modified) (1 prop)
• HeuristicLab.Problems.LawnMower.Views/3.3/HeuristicLab.Problems.LawnMower.Views-3.3.csproj (copied) (copied from trunk/sources/HeuristicLab.Problems.LawnMower.Views/3.3/HeuristicLab.Problems.LawnMower.Views-3.3.csproj)
• HeuristicLab.Problems.LawnMower.Views/3.3/HeuristicLab.Problems.LawnMower.Views.csproj (deleted)
• HeuristicLab.Problems.LawnMower/3.3/HeuristicLab.Problems.LawnMower-3.3.csproj (copied) (copied from trunk/sources/HeuristicLab.Problems.LawnMower/3.3/HeuristicLab.Problems.LawnMower-3.3.csproj)
• HeuristicLab.Problems.LawnMower/3.3/HeuristicLab.Problems.LawnMower.csproj (deleted)
• HeuristicLab.Problems.NK/3.3/HeuristicLab.Problems.NK-3.3.csproj (copied) (copied from trunk/sources/HeuristicLab.Problems.NK/3.3/HeuristicLab.Problems.NK-3.3.csproj)
• HeuristicLab.Problems.NK/3.3/HeuristicLab.Problems.NK.csproj (deleted)
• HeuristicLab.Problems.QuadraticAssignment.Algorithms/3.3/RobustTabooSeachOperator.cs (modified) (6 diffs)
• HeuristicLab.Problems.QuadraticAssignment.Algorithms/3.3/RobustTabooSearch.cs (modified) (3 diffs)
• HeuristicLab.Tests (modified) (1 prop)
• HeuristicLab.Tests/HeuristicLab-3.3/Samples/VnsOpSampleTest.cs (modified) (3 diffs)
• HeuristicLab.Tests/HeuristicLab.Encodings.SymbolicExpressionTreeEncoding-3.4/FullTreeCreatorTest.cs (modified) (1 diff)

branches/crossvalidation-2434/HeuristicLab 3.3.sln

@@ -350 +350 @@
 Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "HeuristicLab.Clients.OKB.Views-3.3", "HeuristicLab.Clients.OKB.Views\3.3\HeuristicLab.Clients.OKB.Views-3.3.csproj", "{399EBB6E-37A1-4AE4-B8CD-0D461FF286A3}"
 EndProject
-Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "HeuristicLab.Problems.LawnMower", "HeuristicLab.Problems.LawnMower\3.3\HeuristicLab.Problems.LawnMower.csproj", "{9A04599C-D608-4240-8DA6-D41F51C515A3}"
-EndProject
-Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "HeuristicLab.Problems.LawnMower.Views", "HeuristicLab.Problems.LawnMower.Views\3.3\HeuristicLab.Problems.LawnMower.Views.csproj", "{71CDE004-C50F-48DF-858E-AB0AAA3537BC}"
+Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "HeuristicLab.Problems.LawnMower-3.3", "HeuristicLab.Problems.LawnMower\3.3\HeuristicLab.Problems.LawnMower-3.3.csproj", "{9A04599C-D608-4240-8DA6-D41F51C515A3}"
+EndProject
+Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "HeuristicLab.Problems.LawnMower.Views-3.3", "HeuristicLab.Problems.LawnMower.Views\3.3\HeuristicLab.Problems.LawnMower.Views-3.3.csproj", "{71CDE004-C50F-48DF-858E-AB0AAA3537BC}"
 EndProject
 Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "HeuristicLab.Algorithms.ScatterSearch-3.3", "HeuristicLab.Algorithms.ScatterSearch\3.3\HeuristicLab.Algorithms.ScatterSearch-3.3.csproj", "{5FEE5DB4-7FD9-4CBD-BEC2-3FEE17B31A94}"
@@ -379 +379 @@
 Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "HeuristicLab.Problems.Instances.Scheduling-3.3", "HeuristicLab.Problems.Instances.Scheduling\3.3\HeuristicLab.Problems.Instances.Scheduling-3.3.csproj", "{9D792B6D-836B-46DC-9D69-50B4B1E7B87F}"
 EndProject
-Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "HeuristicLab.ParallelEngine.Views", "HeuristicLab.ParallelEngine.Views\3.3\HeuristicLab.ParallelEngine.Views.csproj", "{D34A7620-3E23-40D9-8647-637BE901F271}"
+Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "HeuristicLab.ParallelEngine.Views-3.3", "HeuristicLab.ParallelEngine.Views\3.3\HeuristicLab.ParallelEngine.Views-3.3.csproj", "{D34A7620-3E23-40D9-8647-637BE901F271}"
 EndProject
 Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "HeuristicLab.Algorithms.CMAEvolutionStrategy-3.3", "HeuristicLab.Algorithms.CMAEvolutionStrategy\3.3\HeuristicLab.Algorithms.CMAEvolutionStrategy-3.3.csproj", "{5E516C4F-9935-437F-8B15-ECEF4451744E}"
@@ -421 +421 @@
 Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "HeuristicLab.Problems.ExternalEvaluation.Views-3.4", "HeuristicLab.Problems.ExternalEvaluation.Views\3.4\HeuristicLab.Problems.ExternalEvaluation.Views-3.4.csproj", "{F7E5B975-FDF2-45A4-91CB-FF6D3C33D65E}"
 EndProject
-Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "HeuristicLab.Problems.NK", "HeuristicLab.Problems.NK\3.3\HeuristicLab.Problems.NK.csproj", "{C3AD50E6-E717-490E-ABC7-32EF7FB03C97}"
+Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "HeuristicLab.Problems.NK-3.3", "HeuristicLab.Problems.NK\3.3\HeuristicLab.Problems.NK-3.3.csproj", "{C3AD50E6-E717-490E-ABC7-32EF7FB03C97}"
 EndProject
 Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "OutdatedPlugins", "OutdatedPlugins", "{D1B1DE45-F9C7-4FBF-B73C-E759BC4223D5}"

branches/crossvalidation-2434/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesAlgorithm.cs

@@ -233 +233 @@
       // produce solution 
       if (CreateSolution) {
+        var surrogateModel = new GradientBoostedTreesModelSurrogate(problemData, (uint)Seed, lossFunction.ToString(),
+          Iterations, MaxSize, R, M, Nu, state.GetModel());
+
         // for logistic regression we produce a classification solution
         if (lossFunction is LogisticRegressionLoss) {
-          var model = new DiscriminantFunctionClassificationModel(state.GetModel(),
+          var model = new DiscriminantFunctionClassificationModel(surrogateModel,
             new AccuracyMaximizationThresholdCalculator());
           var classificationProblemData = new ClassificationProblemData(problemData.Dataset,
@@ -245 +248 @@
         } else {
           // otherwise we produce a regression solution
-          Results.Add(new Result("Solution", new RegressionSolution(state.GetModel(), problemData)));
+          Results.Add(new Result("Solution", new RegressionSolution(surrogateModel, problemData)));
         }
       }

branches/crossvalidation-2434/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesModel.cs

@@ -34 +34 @@
   // this is essentially a collection of weighted regression models
   public sealed class GradientBoostedTreesModel : NamedItem, IRegressionModel {
-    [Storable]
+    // BackwardsCompatibility3.4 for allowing deserialization & serialization of old models
+    #region Backwards compatible code, remove with 3.5
+    private bool isCompatibilityLoaded = false; // only set to true if the model is deserialized from the old format, needed to make sure that information is serialized again if it was loaded from the old format
+
+    [Storable(Name = "models")]
+    private IList<IRegressionModel> __persistedModels {
+      set {
+        this.isCompatibilityLoaded = true;
+        this.models.Clear();
+        foreach (var m in value) this.models.Add(m);
+      }
+      get { if (this.isCompatibilityLoaded) return models; else return null; }
+    }
+    [Storable(Name = "weights")]
+    private IList<double> __persistedWeights {
+      set {
+        this.isCompatibilityLoaded = true;
+        this.weights.Clear();
+        foreach (var w in value) this.weights.Add(w);
+      }
+      get { if (this.isCompatibilityLoaded) return weights; else return null; }
+    }
+    #endregion
+
     private readonly IList<IRegressionModel> models;
     public IEnumerable<IRegressionModel> Models { get { return models; } }
 
-    [Storable]
     private readonly IList<double> weights;
     public IEnumerable<double> Weights { get { return weights; } }
 
     [StorableConstructor]
-    private GradientBoostedTreesModel(bool deserializing) : base(deserializing) { }
+    private GradientBoostedTreesModel(bool deserializing)
+      : base(deserializing) {
+      models = new List<IRegressionModel>();
+      weights = new List<double>();
+    }
     private GradientBoostedTreesModel(GradientBoostedTreesModel original, Cloner cloner)
       : base(original, cloner) {
       this.weights = new List<double>(original.weights);
       this.models = new List<IRegressionModel>(original.models.Select(m => cloner.Clone(m)));
+      this.isCompatibilityLoaded = original.isCompatibilityLoaded;
     }
     public GradientBoostedTreesModel(IEnumerable<IRegressionModel> models, IEnumerable<double> weights)
@@ -64 +91 @@
       // allocate target array go over all models and add up weighted estimation for each row
       if (!rows.Any()) return Enumerable.Empty<double>(); // return immediately if rows is empty. This prevents multiple iteration over lazy rows enumerable.
-                                                          // (which essentially looks up indexes in a dictionary)
+      // (which essentially looks up indexes in a dictionary)
       var res = new double[rows.Count()];
       for (int i = 0; i < models.Count; i++) {

branches/crossvalidation-2434/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/RegressionTreeModel.cs

@@ -82 +82 @@
     [Storable]
     // to prevent storing the references to data caches in nodes
+    // seemingly it is bad (performance-wise) to persist tuples (tuples are used as keys in a dictionary) TODO
     private Tuple<string, double, int, int>[] SerializedTree {
       get { return tree.Select(t => Tuple.Create(t.VarName, t.Val, t.LeftIdx, t.RightIdx)).ToArray(); }

branches/crossvalidation-2434/HeuristicLab.Algorithms.DataAnalysis/3.4/HeuristicLab.Algorithms.DataAnalysis-3.4.csproj

@@ -195 +195 @@
     <Compile Include="GaussianProcess\GaussianProcessRegressionSolution.cs" />
     <Compile Include="GaussianProcess\ICovarianceFunction.cs" />
+    <Compile Include="GradientBoostedTrees\GradientBoostedTreesModelSurrogate.cs" />
     <Compile Include="GradientBoostedTrees\GradientBoostedTreesAlgorithm.cs" />
     <Compile Include="GradientBoostedTrees\GradientBoostedTreesAlgorithmStatic.cs" />

branches/crossvalidation-2434/HeuristicLab.Analysis.Statistics.Views/3.3/StatisticalTestsView.cs

@@ -275 +275 @@
         data = new double[columnNames.Count()][];
 
+        if (!groups.Any() || !columnNames.Any()) {
+          return;
+        }
+
         DoubleMatrix dt = new DoubleMatrix(groups.Select(x => x.Count()).Max(), columnNames.Count());
         dt.ColumnNames = columnNames;
@@ -311 +315 @@
 
       foreach (string cn in columnNames) {
-        var tmpRuns = runs.Where(x => ((string)((dynamic)x.Parameters[parameterName]).Value.ToString()) == cn);
+        var tmpRuns = runs.Where(x =>
+        x.Parameters.ContainsKey(parameterName) &&
+        (((string)((dynamic)x.Parameters[parameterName]).Value.ToString()) == cn));
         runCols.Add(tmpRuns);
       }
@@ -331 +337 @@
 
     private bool VerifyDataLength(bool showMessage) {
-      if (data == null || data.Length == 0)
+      if (data == null || data.Length < 2)
         return false;
 
@@ -457 +463 @@
       double[][] newData = FilterDataForPairwiseTest(colIndex);
 
-      var rowNames = new[] { "p-Value of Mann-Whitney U", "Adjusted p-Value of Mann-Whitney U", 
+      var rowNames = new[] { "p-Value of Mann-Whitney U", "Adjusted p-Value of Mann-Whitney U",
             "p-Value of T-Test", "Adjusted p-Value of T-Test", "Cohen's d", "Hedges' g" };
 

branches/crossvalidation-2434/HeuristicLab.Encodings.IntegerVectorEncoding/3.3/IntegerVectorEncoding.cs

@@ -130 +130 @@
       }
 
-      LengthParameter = new FixedValueParameter<IntValue>(Name + ".Length", new IntValue(length));
-      BoundsParameter = new ValueParameter<IntMatrix>(Name + ".Bounds", bounds);
+      lengthParameter = new FixedValueParameter<IntValue>(Name + ".Length", new IntValue(length));
+      boundsParameter = new ValueParameter<IntMatrix>(Name + ".Bounds", bounds);
+      Parameters.Add(lengthParameter);
+      Parameters.Add(boundsParameter);
 
       SolutionCreator = new UniformRandomIntegerVectorCreator();

branches/crossvalidation-2434/HeuristicLab.Encodings.RealVectorEncoding/3.3/RealVectorEncoding.cs

@@ -124 +124 @@
         bounds[i, 1] = max[i];
       }
-      LengthParameter = new FixedValueParameter<IntValue>(Name + ".Length", new IntValue(length));
-      BoundsParameter = new ValueParameter<DoubleMatrix>(Name + ".Bounds", bounds);
+      lengthParameter = new FixedValueParameter<IntValue>(Name + ".Length", new IntValue(length));
+      boundsParameter = new ValueParameter<DoubleMatrix>(Name + ".Bounds", bounds);
+      Parameters.Add(lengthParameter);
+      Parameters.Add(boundsParameter);
 
       SolutionCreator = new UniformRandomRealVectorCreator();

branches/crossvalidation-2434/HeuristicLab.Encodings.SymbolicExpressionTreeEncoding/3.4/Creators/FullTreeCreator.cs

@@ -77 +77 @@
       rootNode.AddSubtree(startNode);
 
-      Create(random, startNode, maxTreeDepth - 2);
+      Create(random, startNode, maxTreeDepth-1);
       tree.Root = rootNode;
       return tree;
@@ -99 +99 @@
       for (var i = 0; i < arity; i++) {
         var possibleSymbols = allowedSymbols
-          .Where(s => seedNode.Grammar.IsAllowedChildSymbol(seedNode.Symbol, s, i))
+          .Where(s => seedNode.Grammar.IsAllowedChildSymbol(seedNode.Symbol, s, i)
+                   && seedNode.Grammar.GetMinimumExpressionDepth(s) <= maxDepth
+                   && seedNode.Grammar.GetMaximumExpressionDepth(s) >= maxDepth)
           .ToList();
         var weights = possibleSymbols.Select(s => s.InitialFrequency).ToList();
@@ -142 +144 @@
         var selectedSymbol = possibleSymbols.SelectRandom(weights, random);
 #pragma warning restore 612, 618
-        
+
         var tree = selectedSymbol.CreateTreeNode();
         if (tree.HasLocalParameters) tree.ResetLocalParameters(random);

branches/crossvalidation-2434/HeuristicLab.Encodings.SymbolicExpressionTreeEncoding/3.4/Creators/GrowTreeCreator.cs

@@ -74 +74 @@
       rootNode.AddSubtree(startNode);
 
-      Create(random, startNode, maxTreeDepth - 2);
+      Create(random, startNode, maxTreeDepth - 1);
       tree.Root = rootNode;
       return tree;

branches/crossvalidation-2434/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/TreeMatching/SymbolicExpressionTreePhenotypicSimilarityCalculator.cs

@@ -67 +67 @@
       var r = OnlinePearsonsRCalculator.Calculate(v1, v2, out error);
 
-      if (r > 1.0)
-        r = 1.0;
+      var r2 = error == OnlineCalculatorError.None ? r * r : 0;
 
-      return error == OnlineCalculatorError.None ? r*r : 0;
+      if (r2 > 1.0)
+        r2 = 1.0;
+
+      return r2;
     }
 
@@ -89 +91 @@
       var r = OnlinePearsonsRCalculator.Calculate(leftValues, rightValues, out error);
 
-      if (r > 1.0)
-        r = 1.0; // sometimes due to fp errors it can happen that the correlation is over 1 (like 1.0000000009)
+      var r2 = error == OnlineCalculatorError.None ? r * r : 0;
 
-      return error == OnlineCalculatorError.None ? r*r : 0;
+      if (r2 > 1.0)
+        r2 = 1.0;
+
+      return r2;
     }
   }

branches/crossvalidation-2434/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/Regression/IRegressionSolution.cs

@@ -41 +41 @@
     double TrainingNormalizedMeanSquaredError { get; }
     double TestNormalizedMeanSquaredError { get; }
+    double TrainingRootMeanSquaredError { get; }
+    double TestRootMeanSquaredError { get; }
   }
 }

branches/crossvalidation-2434/HeuristicLab.Problems.QuadraticAssignment.Algorithms/3.3/RobustTabooSeachOperator.cs

@@ -20 +20 @@
 #endregion
 
+using System;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
@@ -92 +93 @@
     }
 
-    public ILookupParameter<IntValue> EvaluatedMovesParameter {
-      get { return (ILookupParameter<IntValue>)Parameters["EvaluatedMoves"]; }
+    public ILookupParameter<IntValue> EvaluatedSolutionsParameter {
+      get { return (ILookupParameter<IntValue>)Parameters["EvaluatedSolutions"]; }
+    }
+
+    public ILookupParameter<DoubleValue> EvaluatedSolutionEquivalentsParameter {
+      get { return (ILookupParameter<DoubleValue>)Parameters["EvaluatedSolutionEquivalents"]; }
     }
     #endregion
@@ -121 +126 @@
       Parameters.Add(new ValueLookupParameter<IntValue>("AlternativeAspirationTenure", "The time t that a move will be remembered for the alternative aspiration condition."));
       Parameters.Add(new LookupParameter<BoolValue>("AllMovesTabu", "Indicates that all moves are tabu."));
-      Parameters.Add(new LookupParameter<IntValue>("EvaluatedMoves", "The number of move evaluations made."));
+      Parameters.Add(new LookupParameter<IntValue>("EvaluatedSolutions", "The number of evaluated solutions."));
+      Parameters.Add(new LookupParameter<DoubleValue>("EvaluatedSolutionEquivalents", "The number of evaluated solution equivalents."));
     }
 
@@ -135 +141 @@
         Parameters.Add(new LookupParameter<BoolValue>("AllMovesTabu", "Indicates that all moves are tabu."));
       }
-      if (!Parameters.ContainsKey("EvaluatedMoves")) {
-        Parameters.Add(new LookupParameter<IntValue>("EvaluatedMoves", "The number of move evaluations made."));
+      if (!Parameters.ContainsKey("EvaluatedSolutions")) {
+        Parameters.Add(new LookupParameter<IntValue>("EvaluatedSolutions", "The number of evaluated solutions."));
+      }
+      if (!Parameters.ContainsKey("EvaluatedSolutionEquivalents")) {
+        Parameters.Add(new LookupParameter<DoubleValue>("EvaluatedSolutionEquivalents", "The number of evaluated solution equivalents."));
       }
       #endregion
@@ -171 +180 @@
       bool already_aspired = false;
 
-      var evaluatedMoves = 0;
+      double evaluations = EvaluatedSolutionEquivalentsParameter.ActualValue.Value;
       foreach (Swap2Move move in ExhaustiveSwap2MoveGenerator.Generate(solution)) {
         double moveQuality;
         if (lastMove == null) {
           moveQuality = QAPSwap2MoveEvaluator.Apply(solution, move, weights, distances);
-          evaluatedMoves++;
+          evaluations += 4.0 / solution.Length;
         } else if (allMovesTabu) moveQuality = moveQualityMatrix[move.Index1, move.Index2];
         else {
           moveQuality = QAPSwap2MoveEvaluator.Apply(solution, move, moveQualityMatrix[move.Index1, move.Index2], weights, distances, lastMove);
-          evaluatedMoves++;
+          if (move.Index1 == lastMove.Index1 || move.Index2 == lastMove.Index1 || move.Index1 == lastMove.Index2 || move.Index2 == lastMove.Index2)
+            evaluations += 4.0 / solution.Length;
+          else evaluations += 2.0 / (solution.Length * solution.Length);
         }
 
@@ -214 +225 @@
       }
 
-      EvaluatedMovesParameter.ActualValue.Value += evaluatedMoves;
+      EvaluatedSolutionEquivalentsParameter.ActualValue.Value = evaluations;
+      EvaluatedSolutionsParameter.ActualValue.Value = (int)Math.Ceiling(evaluations);
 
       allMovesTabu = bestMove == null;

branches/crossvalidation-2434/HeuristicLab.Problems.QuadraticAssignment.Algorithms/3.3/RobustTabooSearch.cs

@@ -168 +168 @@
       VariableCreator variableCreator = new VariableCreator();
       variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Iterations", new IntValue(0)));
-      variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("EvaluatedSolutions", new IntValue(0)));
-      variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("EvaluatedMoves", new IntValue(0)));
+      variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("EvaluatedSolutions", new IntValue(1)));
+      variableCreator.CollectedValues.Add(new ValueParameter<DoubleValue>("EvaluatedSolutionEquivalents", new DoubleValue(1)));
 
       ResultsCollector resultsCollector = new ResultsCollector();
       resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("Iterations", "The actual iteration."));
-      resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("EvaluatedSolutions", "The number of full solution evaluations."));
-      resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("EvaluatedMoves", "The number of move evaluations."));
+      resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("EvaluatedSolutions", "Number of evaluated solutions."));
 
       solutionsCreator = new SolutionsCreator();
       solutionsCreator.NumberOfSolutions = new IntValue(1);
-
-      IntCounter counter = new IntCounter();
-      counter.ValueParameter.ActualName = "EvaluatedSolutions";
-      counter.Increment = new IntValue(1);
 
       Placeholder analyzer = new Placeholder();
@@ -202 +197 @@
       mainOperator.ShortTermMemoryParameter.ActualName = "ShortTermMemory";
       mainOperator.UseAlternativeAspirationParameter.ActualName = UseAlternativeAspirationParameter.Name;
-      mainOperator.EvaluatedMovesParameter.ActualName = "EvaluatedMoves";
+      mainOperator.EvaluatedSolutionsParameter.ActualName = "EvaluatedSolutions";
+      mainOperator.EvaluatedSolutionEquivalentsParameter.ActualName = "EvaluatedSolutionEquivalents";
 
       ConditionalBranch qualityStopBranch = new ConditionalBranch();
@@ -235 +231 @@
       variableCreator.Successor = resultsCollector;
       resultsCollector.Successor = solutionsCreator;
-      solutionsCreator.Successor = counter;
-      counter.Successor = analyzer;
+      solutionsCreator.Successor = analyzer;
       analyzer.Successor = ussp;
       ussp.Operator = mainOperator;

branches/crossvalidation-2434/HeuristicLab.Tests/HeuristicLab-3.3/Samples/VnsOpSampleTest.cs

@@ -37 +37 @@
     [TestCategory("Samples.Create")]
     [TestProperty("Time", "medium")]
-    public void CreateVnsTspSampleTest() {
-      var vns = CreateVnsTspSample();
+    public void CreateVnsOpSampleTest() {
+      var vns = CreateVnsOpSample();
       string path = Path.Combine(SamplesUtils.SamplesDirectory, SampleFileName + SamplesUtils.SampleFileExtension);
       XmlGenerator.Serialize(vns, path);
@@ -45 +45 @@
     [TestCategory("Samples.Execute")]
     [TestProperty("Time", "long")]
-    public void RunVnsTspSampleTest() {
-      var vns = CreateVnsTspSample();
+    public void RunVnsOpSampleTest() {
+      var vns = CreateVnsOpSample();
       vns.SetSeedRandomly = false;
       SamplesUtils.RunAlgorithm(vns);
@@ -55 +55 @@
     }
 
-    private VariableNeighborhoodSearch CreateVnsTspSample() {
+    private VariableNeighborhoodSearch CreateVnsOpSample() {
       VariableNeighborhoodSearch vns = new VariableNeighborhoodSearch();
       #region Problem Configuration

branches/crossvalidation-2434/HeuristicLab.Tests/HeuristicLab.Encodings.SymbolicExpressionTreeEncoding-3.4/FullTreeCreatorTest.cs

@@ -53 +53 @@
       foreach (var tree in randomTrees) {
         Util.IsValid(tree);
-        Assert.IsTrue(tree.Depth == MAX_TREE_DEPTH);
+        Assert.IsTrue(tree.Depth-1 == MAX_TREE_DEPTH);
         if (maxLength < tree.Length)
           maxLength = tree.Length;