Changeset 8010 for branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4

Timestamp:

06/15/12 13:17:07 (12 years ago)

Author:

mkommend

Message:

#1081: Corrected time series solution results and implemented new models.

Location:

branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4

Files:

• Interfaces/ISymbolicTimeSeriesPrognogisExpressionTreeInterpreter.cs (modified) (1 diff)
• SingleObjective/SymbolicTimeSeriesPrognosisSingleObjectiveMeanSquaredErrorEvaluator.cs (modified) (5 diffs)
• SymbolicTimeSeriesPrognosisModel.cs (modified) (1 diff)
• SymbolicTimeSeriesPrognosisSolution.cs (modified) (1 diff)

branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/Interfaces/ISymbolicTimeSeriesPrognogisExpressionTreeInterpreter.cs

@@ -27 +27 @@
     string TargetVariable { get; set; }
     IEnumerable<IEnumerable<double>> GetSymbolicExpressionTreeValues(ISymbolicExpressionTree tree, Dataset dataset, IEnumerable<int> rows, int horizon);
+    IEnumerable<IEnumerable<double>> GetSymbolicExpressionTreeValues(ISymbolicExpressionTree tree, Dataset dataset, IEnumerable<int> rows, IEnumerable<int> horizon);
   }
 }

branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SingleObjective/SymbolicTimeSeriesPrognosisSingleObjectiveMeanSquaredErrorEvaluator.cs

@@ -54 +54 @@
       double quality = Calculate(interpreter, solution,
         EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper,
-        ProblemDataParameter.ActualValue,
-        rows, HorizonParameter.ActualValue.Value, ApplyLinearScaling);
+        ProblemDataParameter.ActualValue, rows, EvaluationPartitionParameter.ActualValue,
+        HorizonParameter.ActualValue.Value, ApplyLinearScaling);
       QualityParameter.ActualValue = new DoubleValue(quality);
 
@@ -61 +61 @@
     }
 
-    public static double Calculate(ISymbolicTimeSeriesPrognosisExpressionTreeInterpreter interpreter, ISymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, ITimeSeriesPrognosisProblemData problemData, IEnumerable<int> rows, int horizon, bool applyLinearScaling) {
-      int horizion2 = problemData.TrainingPartition.End - problemData.TrainingPartition.Start;
-      IEnumerable<double> targetValues = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, rows.Take(1).Select(r => Enumerable.Range(r, horizion2)).First());
-      IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows.Take(1), horizion2).SelectMany(x => x);
+    public static double Calculate(ISymbolicTimeSeriesPrognosisExpressionTreeInterpreter interpreter, ISymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, ITimeSeriesPrognosisProblemData problemData, IEnumerable<int> rows, IntRange evaluationPartition, int horizon, bool applyLinearScaling) {
+      var horizions = rows.Select(r => Math.Min(horizon, evaluationPartition.End - r));
+      IEnumerable<double> targetValues = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, rows.Zip(horizions, Enumerable.Range).SelectMany(r => r));
+      IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows, horizions).SelectMany(x => x);
       IEnumerable<double> boundedEstimatedValues = estimatedValues.LimitToRange(lowerEstimationLimit, upperEstimationLimit);
       OnlineCalculatorError errorState;
@@ -71 +71 @@
       if (applyLinearScaling) {
         var mseCalculator = new OnlineMeanSquaredErrorCalculator();
-        CalculateWithScaling(targetValues, boundedEstimatedValues, mseCalculator, problemData.Dataset.Rows);
+        CalculateWithScaling(targetValues, boundedEstimatedValues, mseCalculator, problemData.Dataset.Rows * horizon);
         errorState = mseCalculator.ErrorState;
         mse = mseCalculator.MeanSquaredError;
@@ -79 +79 @@
       if (errorState != OnlineCalculatorError.None) return Double.NaN;
       else return mse;
+
     }
 
@@ -86 +87 @@
       EstimationLimitsParameter.ExecutionContext = context;
       HorizonParameter.ExecutionContext = context;
+      EvaluationPartitionParameter.ExecutionContext = context;
 
-      double mse = Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue as ISymbolicTimeSeriesPrognosisExpressionTreeInterpreter, tree, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, problemData, rows, HorizonParameter.ActualValue.Value, ApplyLinearScaling);
+      double mse = Calculate((ISymbolicTimeSeriesPrognosisExpressionTreeInterpreter)SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, tree, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, problemData, rows, EvaluationPartitionParameter.ActualValue, HorizonParameter.ActualValue.Value, ApplyLinearScaling);
 
       HorizonParameter.ExecutionContext = null;
       SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = null;
       EstimationLimitsParameter.ExecutionContext = null;
+      EvaluationPartitionParameter.ExecutionContext = null;
 
       return mse;

branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SymbolicTimeSeriesPrognosisModel.cs

@@ -86 +86 @@
     }
 
-    public IEnumerable<IEnumerable<double>> GetPrognosedValues(Dataset dataset, IEnumerable<int> rows, int horizon) {
-      var estimatedValues = Interpreter.GetSymbolicExpressionTreeValues(SymbolicExpressionTree, dataset, rows, horizon);
+    public IEnumerable<IEnumerable<double>> GetPrognosedValues(Dataset dataset, IEnumerable<int> rows, IEnumerable<int> horizons) {
+      var estimatedValues = Interpreter.GetSymbolicExpressionTreeValues(SymbolicExpressionTree, dataset, rows, horizons);
       return estimatedValues.Select(predictionPerRow => predictionPerRow.LimitToRange(lowerEstimationLimit, upperEstimationLimit));
     }

branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SymbolicTimeSeriesPrognosisSolution.cs

@@ -25 +25 @@
 using HeuristicLab.Optimization;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
 
 namespace HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis {