protected override IEnumerable<IRegressionSolution> CreateBaselineSolutions() {
foreach (var sol in base.CreateBaselineSolutions())
yield return sol;
IEnumerable<double> trainingStartValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices.Select(r => r - 1).Where(r => r > 0)).ToList();
//AR1 model
double alpha, beta;
OnlineCalculatorError errorState;
OnlineLinearScalingParameterCalculator.Calculate(ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices.Where(x => x > 0)), trainingStartValues, out alpha, out beta, out errorState);
var ar1Solution = new TimeSeriesPrognosisAutoRegressiveModel(ProblemData.TargetVariable, new double[] { beta }, alpha).CreateTimeSeriesPrognosisSolution(ProblemData);
ar1Solution.Name = "AR(1)";
yield return ar1Solution;
}
protected override IEnumerable <IRegressionSolution> CreateBaselineSolutions()
{
foreach (var sol in base.CreateBaselineSolutions())
{
yield return(sol);
}
IEnumerable <double> trainingStartValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices.Select(r => r - 1).Where(r => r > 0)).ToList();
//AR1 model
double alpha, beta;
OnlineCalculatorError errorState;
OnlineLinearScalingParameterCalculator.Calculate(ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices.Where(x => x > 0)), trainingStartValues, out alpha, out beta, out errorState);
var ar1Solution = new TimeSeriesPrognosisAutoRegressiveModel(ProblemData.TargetVariable, new double[] { beta }, alpha).CreateTimeSeriesPrognosisSolution(ProblemData);
ar1Solution.Name = "AR(1)";
yield return(ar1Solution);
}
