Changeset 13791 for branches/PerformanceComparison/HeuristicLab.OptimizationExpertSystem.Common/3.3/Recommenders/OverallBestRecommender.cs

Timestamp:

04/25/16 12:56:17 (8 years ago)

Author:

abeham

Message:

#2457: working on recommendation algorithms

File:

• branches/PerformanceComparison/HeuristicLab.OptimizationExpertSystem.Common/3.3/Recommenders/OverallBestRecommender.cs (modified) (4 diffs)

branches/PerformanceComparison/HeuristicLab.OptimizationExpertSystem.Common/3.3/Recommenders/OverallBestRecommender.cs

@@ -25 +25 @@
 using HeuristicLab.Data;
 using HeuristicLab.Optimization;
-using HeuristicLab.Parameters;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
 using System;
@@ -39 +38 @@
       get { return (IFixedValueParameter<DoubleValue>)Parameters["NeighborhoodFactor"]; }
     }
-
-    public double NeighborhoodFactor {
-      get { return NeighborhoodFactorParameter.Value.Value; }
-      set { NeighborhoodFactorParameter.Value.Value = value; }
-    }
     
     [StorableConstructor]
     private OverallBestRecommender(bool deserializing) : base(deserializing) { }
-    private OverallBestRecommender(OverallBestRecommender original, Cloner cloner)
-      : base(original, cloner) { }
-    public OverallBestRecommender() {
-      Parameters.Add(new FixedValueParameter<DoubleValue>("NeighborhoodFactor", "Penalize neighbors that are far away.", new DoubleValue(5)));
-    }
+    private OverallBestRecommender(OverallBestRecommender original, Cloner cloner) : base(original, cloner) { }
+    public OverallBestRecommender() { }
 
     public override IDeepCloneable Clone(Cloner cloner) {
@@ -57 +48 @@
     }
 
-    public IRecommendationModel TrainModel(KnowledgeCenter kc, string[] characteristics) {
+    public IRecommendationModel TrainModel(IRun[] problemInstances, KnowledgeCenter kc, string[] characteristics) {
       var instances = new List<Tuple<IAlgorithm, double>>();
       foreach (var relevantRuns in kc.GetKnowledgeBaseByAlgorithm()) {
         var algorithm = relevantRuns.Key;
         var pis = relevantRuns.Value.Select(x => ((StringValue)x.Parameters["Problem Name"]).Value).Distinct()
-                              .Select(x => Tuple.Create(x, kc.ProblemInstances.SingleOrDefault(y => ((StringValue)y.Parameters["Problem Name"]).Value == x)))
+                              .Select(x => Tuple.Create(x, problemInstances.SingleOrDefault(y => ((StringValue)y.Parameters["Problem Name"]).Value == x)))
                               .Where(x => x.Item2 != null)
                               .Select(x => Tuple.Create(x.Item1, ((DoubleValue)x.Item2.Parameters["BestKnownQuality"]).Value))
@@ -70 +61 @@
         foreach (var problemRuns in relevantRuns.Value.GroupBy(x => ((StringValue)x.Parameters["Problem Name"]).Value)) {
           var bkq = pis[problemRuns.Key];
-          var ert = ExpectedRuntimeHelper.CalculateErt(problemRuns.ToList(), "QualityPerEvaluations", (kc.Maximization ? (1 - kc.MinimumTarget.Value) : (1 + kc.MinimumTarget.Value)) * bkq, kc.Maximization).ExpectedRuntime;
+          var ert = ExpectedRuntimeHelper.CalculateErt(problemRuns.ToList(), "QualityPerEvaluations", kc.GetTarget(bkq, kc.Maximization), kc.Maximization).ExpectedRuntime;
           if (double.IsNaN(ert)) ert = int.MaxValue;
           avgERT += ert;