public override IRegressionModel Build(IRegressionProblemData pd, IRandom random, CancellationToken cancellationToken, out int numberOfParameters)
{
if (pd.Dataset.Rows < MinLeafSize(pd))
{
throw new ArgumentException("The number of training instances is too small to create a linear model");
}
numberOfParameters = pd.AllowedInputVariables.Count() + 1;
double x1, x2;
var coeffs = ElasticNetLinearRegression.CalculateModelCoefficients(pd, 1, 0.2, out x1, out x2);
numberOfParameters = coeffs.Length;
return(ElasticNetLinearRegression.CreateSymbolicSolution(coeffs, pd).Model);
}
