Changeset 16308 for branches/2845_EnhancedProgress/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective

Timestamp:

11/20/18 13:52:40 (6 years ago)

Author:

pfleck

Message:

#2845 reverted the last merge (r16307) because some revisions were missing

Location:

branches/2845_EnhancedProgress

Files:

• . (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4 (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/ConstantOptimizationAnalyzer.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators/SymbolicRegressionConstantOptimizationEvaluator.cs (modified) (16 diffs)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators/SymbolicRegressionLogResidualEvaluator.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators/SymbolicRegressionMeanRelativeErrorEvaluator.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators/SymbolicRegressionSingleObjectiveEvaluator.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators/SymbolicRegressionSingleObjectiveMaxAbsoluteErrorEvaluator.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators/SymbolicRegressionSingleObjectiveMeanAbsoluteErrorEvaluator.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators/SymbolicRegressionSingleObjectiveMeanSquaredErrorEvaluator.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators/SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveOverfittingAnalyzer.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveProblem.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveTrainingBestSolutionAnalyzer.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveTrainingParetoBestSolutionAnalyzer.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveValidationBestSolutionAnalyzer.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveValidationParetoBestSolutionAnalyzer.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSolutionsAnalyzer.cs (modified) (1 diff)

branches/2845_EnhancedProgress/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/ConstantOptimizationAnalyzer.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.

branches/2845_EnhancedProgress/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators/SymbolicRegressionConstantOptimizationEvaluator.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.
@@ -27 +27 @@
 using HeuristicLab.Data;
 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
-using HeuristicLab.Optimization;
 using HeuristicLab.Parameters;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
@@ -42 +41 @@
     private const string UpdateVariableWeightsParameterName = "Update Variable Weights";
 
-    private const string FunctionEvaluationsResultParameterName = "Constants Optimization Function Evaluations";
-    private const string GradientEvaluationsResultParameterName = "Constants Optimization Gradient Evaluations";
-    private const string CountEvaluationsParameterName = "Count Function and Gradient Evaluations";
-
     public IFixedValueParameter<IntValue> ConstantOptimizationIterationsParameter {
       get { return (IFixedValueParameter<IntValue>)Parameters[ConstantOptimizationIterationsParameterName]; }
@@ -63 +58 @@
     public IFixedValueParameter<BoolValue> UpdateVariableWeightsParameter {
       get { return (IFixedValueParameter<BoolValue>)Parameters[UpdateVariableWeightsParameterName]; }
-    }
-
-    public IResultParameter<IntValue> FunctionEvaluationsResultParameter {
-      get { return (IResultParameter<IntValue>)Parameters[FunctionEvaluationsResultParameterName]; }
-    }
-    public IResultParameter<IntValue> GradientEvaluationsResultParameter {
-      get { return (IResultParameter<IntValue>)Parameters[GradientEvaluationsResultParameterName]; }
-    }
-    public IFixedValueParameter<BoolValue> CountEvaluationsParameter {
-      get { return (IFixedValueParameter<BoolValue>)Parameters[CountEvaluationsParameterName]; }
     }
 
@@ -96 +81 @@
       get { return UpdateVariableWeightsParameter.Value.Value; }
       set { UpdateVariableWeightsParameter.Value.Value = value; }
-    }
-
-    public bool CountEvaluations {
-      get { return CountEvaluationsParameter.Value.Value; }
-      set { CountEvaluationsParameter.Value.Value = value; }
     }
 
@@ -120 +100 @@
       Parameters.Add(new FixedValueParameter<BoolValue>(UpdateConstantsInTreeParameterName, "Determines if the constants in the tree should be overwritten by the optimized constants.", new BoolValue(true)) { Hidden = true });
       Parameters.Add(new FixedValueParameter<BoolValue>(UpdateVariableWeightsParameterName, "Determines if the variable weights in the tree should be  optimized.", new BoolValue(true)) { Hidden = true });
-
-      Parameters.Add(new FixedValueParameter<BoolValue>(CountEvaluationsParameterName, "Determines if function and gradient evaluation should be counted.", new BoolValue(false)));
-      Parameters.Add(new ResultParameter<IntValue>(FunctionEvaluationsResultParameterName, "The number of function evaluations performed by the constants optimization evaluator", "Results", new IntValue()));
-      Parameters.Add(new ResultParameter<IntValue>(GradientEvaluationsResultParameterName, "The number of gradient evaluations performed by the constants optimization evaluator", "Results", new IntValue()));
     }
 
@@ -136 +112 @@
       if (!Parameters.ContainsKey(UpdateVariableWeightsParameterName))
         Parameters.Add(new FixedValueParameter<BoolValue>(UpdateVariableWeightsParameterName, "Determines if the variable weights in the tree should be  optimized.", new BoolValue(true)));
-
-      if (!Parameters.ContainsKey(CountEvaluationsParameterName))
-        Parameters.Add(new FixedValueParameter<BoolValue>(CountEvaluationsParameterName, "Determines if function and gradient evaluation should be counted.", new BoolValue(false)));
-
-      if (!Parameters.ContainsKey(FunctionEvaluationsResultParameterName))
-        Parameters.Add(new ResultParameter<IntValue>(FunctionEvaluationsResultParameterName, "The number of function evaluations performed by the constants optimization evaluator", "Results", new IntValue()));
-      if (!Parameters.ContainsKey(GradientEvaluationsResultParameterName))
-        Parameters.Add(new ResultParameter<IntValue>(GradientEvaluationsResultParameterName, "The number of gradient evaluations performed by the constants optimization evaluator", "Results", new IntValue()));
-    }
-
-    private static readonly object locker = new object();
+    }
+
     public override IOperation InstrumentedApply() {
       var solution = SymbolicExpressionTreeParameter.ActualValue;
@@ -152 +119 @@
       if (RandomParameter.ActualValue.NextDouble() < ConstantOptimizationProbability.Value) {
         IEnumerable<int> constantOptimizationRows = GenerateRowsToEvaluate(ConstantOptimizationRowsPercentage.Value);
-        var counter = new EvaluationsCounter();
         quality = OptimizeConstants(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, solution, ProblemDataParameter.ActualValue,
-           constantOptimizationRows, ApplyLinearScalingParameter.ActualValue.Value, ConstantOptimizationIterations.Value, updateVariableWeights: UpdateVariableWeights, lowerEstimationLimit: EstimationLimitsParameter.ActualValue.Lower, upperEstimationLimit: EstimationLimitsParameter.ActualValue.Upper, updateConstantsInTree: UpdateConstantsInTree, counter: counter);
+           constantOptimizationRows, ApplyLinearScalingParameter.ActualValue.Value, ConstantOptimizationIterations.Value, updateVariableWeights: UpdateVariableWeights, lowerEstimationLimit: EstimationLimitsParameter.ActualValue.Lower, upperEstimationLimit: EstimationLimitsParameter.ActualValue.Upper, updateConstantsInTree: UpdateConstantsInTree);
 
         if (ConstantOptimizationRowsPercentage.Value != RelativeNumberOfEvaluatedSamplesParameter.ActualValue.Value) {
@@ -160 +126 @@
           quality = SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, solution, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, ProblemDataParameter.ActualValue, evaluationRows, ApplyLinearScalingParameter.ActualValue.Value);
         }
-
-        if (CountEvaluations) {
-          lock (locker) {
-            FunctionEvaluationsResultParameter.ActualValue.Value += counter.FunctionEvaluations;
-            GradientEvaluationsResultParameter.ActualValue.Value += counter.GradientEvaluations;
-          }
-        }
-
       } else {
         var evaluationRows = GenerateRowsToEvaluate();
@@ -181 +139 @@
       EstimationLimitsParameter.ExecutionContext = context;
       ApplyLinearScalingParameter.ExecutionContext = context;
-      FunctionEvaluationsResultParameter.ExecutionContext = context;
-      GradientEvaluationsResultParameter.ExecutionContext = context;
 
       // Pearson R² evaluator is used on purpose instead of the const-opt evaluator, 
@@ -192 +148 @@
       EstimationLimitsParameter.ExecutionContext = null;
       ApplyLinearScalingParameter.ExecutionContext = null;
-      FunctionEvaluationsResultParameter.ExecutionContext = null;
-      GradientEvaluationsResultParameter.ExecutionContext = null;
 
       return r2;
-    }
-
-    public class EvaluationsCounter {
-      public int FunctionEvaluations = 0;
-      public int GradientEvaluations = 0;
     }
 
@@ -207 +156 @@
       int maxIterations, bool updateVariableWeights = true,
       double lowerEstimationLimit = double.MinValue, double upperEstimationLimit = double.MaxValue,
-      bool updateConstantsInTree = true, Action<double[], double, object> iterationCallback = null, EvaluationsCounter counter = null) {
+      bool updateConstantsInTree = true, Action<double[], double, object> iterationCallback = null) {
 
       // numeric constants in the tree become variables for constant opt
@@ -219 +168 @@
       TreeToAutoDiffTermConverter.ParametricFunction func;
       TreeToAutoDiffTermConverter.ParametricFunctionGradient func_grad;
-      if (!TreeToAutoDiffTermConverter.TryConvertToAutoDiff(tree, updateVariableWeights, applyLinearScaling, out parameters, out initialConstants, out func, out func_grad))
+      if (!TreeToAutoDiffTermConverter.TryConvertToAutoDiff(tree, updateVariableWeights, out parameters, out initialConstants, out func, out func_grad))
         throw new NotSupportedException("Could not optimize constants of symbolic expression tree due to not supported symbols used in the tree.");
       if (parameters.Count == 0) return 0.0; // gkronber: constant expressions always have a R² of 0.0 
+
       var parameterEntries = parameters.ToArray(); // order of entries must be the same for x
 
       //extract inital constants
-      double[] c;
-      if (applyLinearScaling) {
-        c = new double[initialConstants.Length + 2];
+      double[] c = new double[initialConstants.Length + 2];
+      {
         c[0] = 0.0;
         c[1] = 1.0;
         Array.Copy(initialConstants, 0, c, 2, initialConstants.Length);
-      } else {
-        c = (double[])initialConstants.Clone();
-      }
-
+      }
+      double[] originalConstants = (double[])c.Clone();
       double originalQuality = SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.Calculate(interpreter, tree, lowerEstimationLimit, upperEstimationLimit, problemData, rows, applyLinearScaling);
-
-      if (counter == null) counter = new EvaluationsCounter();
-      var rowEvaluationsCounter = new EvaluationsCounter();
 
       alglib.lsfitstate state;
@@ -273 +217 @@
         alglib.lsfitsetxrep(state, iterationCallback != null);
         //alglib.lsfitsetgradientcheck(state, 0.001);
-        alglib.lsfitfit(state, function_cx_1_func, function_cx_1_grad, xrep, rowEvaluationsCounter);
+        alglib.lsfitfit(state, function_cx_1_func, function_cx_1_grad, xrep, null);
         alglib.lsfitresults(state, out retVal, out c, out rep);
-      } catch (ArithmeticException) {
+      }
+      catch (ArithmeticException) {
         return originalQuality;
-      } catch (alglib.alglibexception) {
+      }
+      catch (alglib.alglibexception) {
         return originalQuality;
       }
 
-      counter.FunctionEvaluations += rowEvaluationsCounter.FunctionEvaluations / n;
-      counter.GradientEvaluations += rowEvaluationsCounter.GradientEvaluations / n;
-
       //retVal == -7  => constant optimization failed due to wrong gradient
-      if (retVal != -7) {
-        if (applyLinearScaling) {
-          var tmp = new double[c.Length - 2];
-          Array.Copy(c, 2, tmp, 0, tmp.Length);
-          UpdateConstants(tree, tmp, updateVariableWeights);
-        } else UpdateConstants(tree, c, updateVariableWeights);
-      }
+      if (retVal != -7) UpdateConstants(tree, c.Skip(2).ToArray(), updateVariableWeights);
       var quality = SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.Calculate(interpreter, tree, lowerEstimationLimit, upperEstimationLimit, problemData, rows, applyLinearScaling);
 
-      if (!updateConstantsInTree) UpdateConstants(tree, initialConstants, updateVariableWeights);
-
+      if (!updateConstantsInTree) UpdateConstants(tree, originalConstants.Skip(2).ToArray(), updateVariableWeights);
       if (originalQuality - quality > 0.001 || double.IsNaN(quality)) {
-        UpdateConstants(tree, initialConstants, updateVariableWeights);
+        UpdateConstants(tree, originalConstants.Skip(2).ToArray(), updateVariableWeights);
         return originalQuality;
       }
@@ -323 +259 @@
       return (double[] c, double[] x, ref double fx, object o) => {
         fx = func(c, x);
-        var counter = (EvaluationsCounter)o;
-        counter.FunctionEvaluations++;
       };
     }
@@ -330 +264 @@
     private static alglib.ndimensional_pgrad CreatePGrad(TreeToAutoDiffTermConverter.ParametricFunctionGradient func_grad) {
       return (double[] c, double[] x, ref double fx, double[] grad, object o) => {
-        var tuple = func_grad(c, x);
-        fx = tuple.Item2;
-        Array.Copy(tuple.Item1, grad, grad.Length);
-        var counter = (EvaluationsCounter)o;
-        counter.GradientEvaluations++;
+        var tupel = func_grad(c, x);
+        fx = tupel.Item2;
+        Array.Copy(tupel.Item1, grad, grad.Length);
       };
     }

branches/2845_EnhancedProgress/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators/SymbolicRegressionLogResidualEvaluator.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.

branches/2845_EnhancedProgress/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators/SymbolicRegressionMeanRelativeErrorEvaluator.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.

branches/2845_EnhancedProgress/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators/SymbolicRegressionSingleObjectiveEvaluator.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.

branches/2845_EnhancedProgress/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators/SymbolicRegressionSingleObjectiveMaxAbsoluteErrorEvaluator.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.

branches/2845_EnhancedProgress/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators/SymbolicRegressionSingleObjectiveMeanAbsoluteErrorEvaluator.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.

branches/2845_EnhancedProgress/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators/SymbolicRegressionSingleObjectiveMeanSquaredErrorEvaluator.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.

branches/2845_EnhancedProgress/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators/SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.

branches/2845_EnhancedProgress/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveOverfittingAnalyzer.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.

branches/2845_EnhancedProgress/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveProblem.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.

branches/2845_EnhancedProgress/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveTrainingBestSolutionAnalyzer.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.

branches/2845_EnhancedProgress/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveTrainingParetoBestSolutionAnalyzer.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.

branches/2845_EnhancedProgress/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveValidationBestSolutionAnalyzer.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.

branches/2845_EnhancedProgress/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveValidationParetoBestSolutionAnalyzer.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.

branches/2845_EnhancedProgress/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSolutionsAnalyzer.cs

@@ -2 +2 @@
 
 /* HeuristicLab
- * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.