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);
}