# Why is a parametric classifier faster to train than a non-parametric one?

In the tutorial Parametric and Nonparametric Machine Learning Algorithms it says that parametric classifiers are faster than non-parametric classifiers. The reason that non-parametric classifiers are slower is because they often have far more parameters to train.

What else could cause this to be true?

• Nearest neighbours is a non parametric classifier with essentially no training time. However at test time you have to find the nearest neighbour... – seanv507 Dec 18 '16 at 18:14
• That appears to be somewhat oversimplifying.... Also the wording "non-parametric classifiers are slower is because they often have far more parameters" (emphasis mine) is a bit funny... In $k$-NN regression you learn a single parameter $k$, while in even a simple univariate least squares you learn two parameters (slope and intercept) so clearly it is not just the number of parameters you care about. – usεr11852 says Reinstate Monic Dec 18 '16 at 18:54