protected override ITimeSeriesPrognosisProblemData ImportData(string path, TimeSeriesPrognosisImportType type, TableFileParser csvFileParser) { Dataset dataset = new Dataset(csvFileParser.VariableNames, csvFileParser.Values); // turn of input variables that are constant in the training partition var allowedInputVars = new List<string>(); int trainingPartEnd = (csvFileParser.Rows * type.TrainingPercentage) / 100; trainingPartEnd = trainingPartEnd > 0 ? trainingPartEnd : 1; var trainingIndizes = Enumerable.Range(0, trainingPartEnd); if (trainingIndizes.Count() >= 2) { foreach (var variableName in dataset.DoubleVariables) { if (dataset.GetDoubleValues(variableName, trainingIndizes).Range() > 0 && variableName != type.TargetVariable) allowedInputVars.Add(variableName); } } else { allowedInputVars.AddRange(dataset.DoubleVariables.Where(x => !x.Equals(type.TargetVariable))); } TimeSeriesPrognosisProblemData timeSeriesPrognosisData = new TimeSeriesPrognosisProblemData(dataset, allowedInputVars, type.TargetVariable); timeSeriesPrognosisData.TrainingPartition.Start = 0; timeSeriesPrognosisData.TrainingPartition.End = trainingPartEnd; timeSeriesPrognosisData.TestPartition.Start = trainingPartEnd; timeSeriesPrognosisData.TestPartition.End = csvFileParser.Rows; timeSeriesPrognosisData.Name = Path.GetFileName(path); return timeSeriesPrognosisData; }
protected override ITimeSeriesPrognosisProblemData ImportData(string path, TimeSeriesPrognosisImportType type, TableFileParser csvFileParser) { Dataset dataset = new Dataset(csvFileParser.VariableNames, csvFileParser.Values); // turn of input variables that are constant in the training partition var allowedInputVars = new List <string>(); int trainingPartEnd = (csvFileParser.Rows * type.TrainingPercentage) / 100; trainingPartEnd = trainingPartEnd > 0 ? trainingPartEnd : 1; var trainingIndizes = Enumerable.Range(0, trainingPartEnd); if (trainingIndizes.Count() >= 2) { foreach (var variableName in dataset.DoubleVariables) { if (dataset.GetDoubleValues(variableName, trainingIndizes).Range() > 0 && variableName != type.TargetVariable) { allowedInputVars.Add(variableName); } } } else { allowedInputVars.AddRange(dataset.DoubleVariables.Where(x => !x.Equals(type.TargetVariable))); } TimeSeriesPrognosisProblemData timeSeriesPrognosisData = new TimeSeriesPrognosisProblemData(dataset, allowedInputVars, type.TargetVariable); timeSeriesPrognosisData.TrainingPartition.Start = 0; timeSeriesPrognosisData.TrainingPartition.End = trainingPartEnd; timeSeriesPrognosisData.TestPartition.Start = trainingPartEnd; timeSeriesPrognosisData.TestPartition.End = csvFileParser.Rows; timeSeriesPrognosisData.Name = Path.GetFileName(path); return(timeSeriesPrognosisData); }