The KNN method is a method that can be used for both regression and classification problems. It belongs to the class of non-parametric models, because, unlike parametric models, the predictions are not based on the calculation of any parameters. Examples of parametric models are the regression models that we just discussed. The weights in the case of the former regression models are the parameters. KNN belongs to the family of non-parametric models, and despite its simplicity (or perhaps because of it), it frequently produces very good results, comparable to those produced by more complex and elaborate models. In its most basic implementation, it is easy understand how to it works: for a fixed number, K, which is the number of neighbors, and a given observation whose target value we want to predict, do the following:
- Find the K data points that are closest in their feature...
