public static Vector <double> GenerateToyData(int seed, Vector <double> x_train)
{
var generater = RndGenerater.Build(seed);
Func <double> noise = () => generater.NextNormal(NoiseNormalMean, NoiseNormalStddev);
return(ToyDataGenerater.Generate2D(Fig_1_2_func, noise, x_train));
}
private static (int, LinearRegressionResult.CalibratedData) Predict(LinearRegressionResult.GivenData data, int polynomialDegree)
{
IFeature feature = new PolynomialFeature(polynomialDegree);
Matrix <double> designMatrix = ToyDataGenerater.DesignMatrix(data.X_train, feature);
Matrix <double> invDesignMatrix = designMatrix.PseudoInverse();
Vector <double> weights = invDesignMatrix * data.T_train;
Vector <double> t_test = Predicts(data.X_test, weights, feature);
return(polynomialDegree, new LinearRegressionResult.CalibratedData(t_test, weights));
}