Changeset 14029 for branches/crossvalidation-2434/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis
- Timestamp:
- 07/08/16 14:40:02 (8 years ago)
- Location:
- branches/crossvalidation-2434
- Files:
-
- 1 deleted
- 9 edited
Legend:
- Unmodified
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branches/crossvalidation-2434
- Property svn:mergeinfo changed
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branches/crossvalidation-2434/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis
- Property svn:mergeinfo changed
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branches/crossvalidation-2434/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/Plugin.cs.frame
r12753 r14029 26 26 27 27 namespace HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis { 28 [Plugin("HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis","Provides classes to perform symbolic time-series prognosis.", "3.4. 8.$WCREV$")]28 [Plugin("HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis","Provides classes to perform symbolic time-series prognosis.", "3.4.9.$WCREV$")] 29 29 [PluginFile("HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis-3.4.dll", PluginFileType.Assembly)] 30 30 [PluginDependency("HeuristicLab.ALGLIB", "3.7.0")] -
branches/crossvalidation-2434/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/Properties/AssemblyInfo.cs.frame
r12753 r14029 53 53 // by using the '*' as shown below: 54 54 [assembly: AssemblyVersion("3.4.0.0")] 55 [assembly: AssemblyFileVersion("3.4. 8.$WCREV$")]55 [assembly: AssemblyFileVersion("3.4.9.$WCREV$")] -
branches/crossvalidation-2434/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SingleObjective/SymbolicTimeSeriesPrognosisSingleObjectiveMeanSquaredErrorEvaluator.cs
r12012 r14029 72 72 mse = mseCalculator.MeanSquaredError; 73 73 } else if (applyLinearScaling) { //first create model to perform linear scaling and afterwards calculate fitness for the scaled model 74 var model = new SymbolicTimeSeriesPrognosisModel( (ISymbolicExpressionTree)solution.Clone(), interpreter, lowerEstimationLimit, upperEstimationLimit);74 var model = new SymbolicTimeSeriesPrognosisModel(problemData.TargetVariable, (ISymbolicExpressionTree)solution.Clone(), interpreter, lowerEstimationLimit, upperEstimationLimit); 75 75 model.Scale(problemData); 76 76 var scaledSolution = model.SymbolicExpressionTree; -
branches/crossvalidation-2434/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SingleObjective/SymbolicTimeSeriesPrognosisSingleObjectiveTrainingBestSolutionAnalyzer.cs
r12012 r14029 64 64 65 65 protected override ISymbolicTimeSeriesPrognosisSolution CreateSolution(ISymbolicExpressionTree bestTree, double bestQuality) { 66 var model = new SymbolicTimeSeriesPrognosisModel( (ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue as ISymbolicTimeSeriesPrognosisExpressionTreeInterpreter, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);66 var model = new SymbolicTimeSeriesPrognosisModel(ProblemDataParameter.ActualValue.TargetVariable, (ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue as ISymbolicTimeSeriesPrognosisExpressionTreeInterpreter, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper); 67 67 if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue); 68 68 return new SymbolicTimeSeriesPrognosisSolution(model, (ITimeSeriesPrognosisProblemData)ProblemDataParameter.ActualValue.Clone()); -
branches/crossvalidation-2434/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SingleObjective/SymbolicTimeSeriesPrognosisSingleObjectiveValidationBestSolutionAnalyzer.cs
r12012 r14029 52 52 53 53 protected override ISymbolicTimeSeriesPrognosisSolution CreateSolution(ISymbolicExpressionTree bestTree, double bestQuality) { 54 var model = new SymbolicTimeSeriesPrognosisModel( (ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue as ISymbolicTimeSeriesPrognosisExpressionTreeInterpreter, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);54 var model = new SymbolicTimeSeriesPrognosisModel(ProblemDataParameter.ActualValue.TargetVariable, (ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue as ISymbolicTimeSeriesPrognosisExpressionTreeInterpreter, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper); 55 55 if (ApplyLinearScalingParameter.ActualValue.Value) model.Scale(ProblemDataParameter.ActualValue); 56 56 -
branches/crossvalidation-2434/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SymbolicTimeSeriesPrognosisExpressionTreeInterpreter.cs
r12509 r14029 73 73 } 74 74 75 private readonly object syncRoot = new object(); 75 76 public IEnumerable<IEnumerable<double>> GetSymbolicExpressionTreeValues(ISymbolicExpressionTree tree, IDataset dataset, IEnumerable<int> rows, IEnumerable<int> horizons) { 76 if (CheckExpressionsWithIntervalArithmetic .Value)77 if (CheckExpressionsWithIntervalArithmetic) 77 78 throw new NotSupportedException("Interval arithmetic is not yet supported in the symbolic data analysis interpreter."); 78 79 if (targetVariableCache == null || targetVariableCache.GetLength(0) < dataset.Rows) … … 82 83 83 84 string targetVariable = TargetVariable; 84 lock ( EvaluatedSolutions) {85 EvaluatedSolutions .Value++; // increment the evaluated solutions counter85 lock (syncRoot) { 86 EvaluatedSolutions++; // increment the evaluated solutions counter 86 87 } 87 88 var state = PrepareInterpreterState(tree, dataset, targetVariableCache, TargetVariable); -
branches/crossvalidation-2434/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SymbolicTimeSeriesPrognosisModel.cs
r12509 r14029 47 47 } 48 48 49 public SymbolicTimeSeriesPrognosisModel( ISymbolicExpressionTree tree, ISymbolicTimeSeriesPrognosisExpressionTreeInterpreter interpreter, double lowerLimit = double.MinValue, double upperLimit = double.MaxValue) : base(tree, interpreter, lowerLimit, upperLimit) { }49 public SymbolicTimeSeriesPrognosisModel(string targetVariable, ISymbolicExpressionTree tree, ISymbolicTimeSeriesPrognosisExpressionTreeInterpreter interpreter, double lowerLimit = double.MinValue, double upperLimit = double.MaxValue) : base(targetVariable, tree, interpreter, lowerLimit, upperLimit) { } 50 50 51 51 public IEnumerable<IEnumerable<double>> GetPrognosedValues(IDataset dataset, IEnumerable<int> rows, IEnumerable<int> horizons) {
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