Changeset 14686 for branches/OptimizationNetworks

Timestamp:

02/17/17 15:54:27 (7 years ago)

Author:

mkommend

Message:

#2205: Updated FeatureSelectionOrchestrator.

File:

• branches/OptimizationNetworks/HeuristicLab.Networks.IntegratedOptimization.MachineLearning/FeatureSelectionOrchestrator.cs (modified) (3 diffs)

branches/OptimizationNetworks/HeuristicLab.Networks.IntegratedOptimization.MachineLearning/FeatureSelectionOrchestrator.cs

@@ -105 +105 @@
       var orchestrationMessage = RegressionOrchestrationPort.PrepareMessage();
       orchestrationMessage["Problem"] = new RegressionProblem() { ProblemData = problemData };
-      orchestrationMessage["OrchestrationMessage"] = new EnumValue<OrchestrationMessage>(OrchestrationMessage.Prepare);
+      orchestrationMessage["OrchestrationMessage"] = new EnumValue<OrchestrationMessage>(OrchestrationMessage.Prepare | OrchestrationMessage.ClearRuns);
       RegressionOrchestrationPort.SendMessage(orchestrationMessage, token);
 
@@ -115 +115 @@
 
       var regressionSolution = results.Select(r => r.Value).OfType<IRegressionSolution>().First();
+      double quality = regressionSolution.TestMeanAbsoluteError;
 
       UpdatedResults(binaryVector, regressionSolution);
-
-
-      double quality = regressionSolution.TestMeanAbsoluteError;
       evaluationMessage["Quality"] = new DoubleValue(quality);
     }
 
     private void UpdatedResults(BinaryVector binaryVector, IRegressionSolution solution) {
-      if (!Results.ContainsKey("Best Solution Vector")) {
-        Results.Add(new Result("Best Solution Vector", typeof(BinaryVector)));
-        //Results.Add(new Result("Best Solution Variables", typeof(DoubleArray)));
-        Results.Add(new Result("Best Symbolic Solution", typeof(IRegressionSolution)));
-      }
+      if (!Results.ContainsKey("Best Vector")) Results.Add(new Result("Best Vector", typeof(BinaryVector)));
+      if (!Results.ContainsKey("Best Solution")) Results.Add(new Result("Best Solution", typeof(IRegressionSolution)));
 
-      var previousBestVector = (BinaryVector)Results["Best Solution Vector"].Value;
+      var previousBestVector = (BinaryVector)Results["Best Vector"].Value;
+      var prevoiusBestSolution = (IRegressionSolution)Results["Best Solution"].Value;
 
-      //check if better vector has been found
-      if (previousBestVector != null && binaryVector.SequenceEqual(previousBestVector))
+      //check if better vector & solution has been found
+      if (prevoiusBestSolution != null && prevoiusBestSolution.TestMeanAbsoluteError < solution.TestMeanAbsoluteError)
         return;
 
-      Results["Best Solution Vector"].Value = binaryVector;
-      Results["Best Symbolic Solution"].Value = solution;
-
-      //var variableNames = solution.ProblemData.AllowedInputVariables;
-      //alglib.linearmodel lm = BuildModel(best, problemData);
-
-      //double[] coefficients = null;
-      //int nFeatures = -1;
-      //alglib.lrunpack(lm, out coefficients, out nFeatures);
-
-      //var doubleArray = new DoubleArray(coefficients.ToArray());
-      //doubleArray.ElementNames = variableNames;
-      //Results["Best Solution Variables"].Value = doubleArray;
-
-
+      Results["Best Vector"].Value = binaryVector;
+      Results["Best Solution"].Value = solution;
     }
 
@@ -156 +139 @@
     //TODO Remove methods
     public override void Pause() { network.Pause(); }
-    public override void Prepare(bool clearRuns = false) { network.Prepare(clearRuns); }
+    public override void Prepare(bool clearRuns = false) { network.Prepare(clearRuns); Results.Clear(); }
     public override void Start() { network.Start(); }
     public override void Stop() { network.Stop(); }