Nearest-Neighbor Methods

Nearest-neighbor methods use those observations in the training set T closest in input space to x  form Y-hat.

Specifically, the k-nearest neighbor fit for Y-hat is difined as follows: Y(x)=1/kΣy_i,x_i belong to N_k(x).

where N_k(x) is the neighborhood of x defined by the k closest points x_i in the traing sample.

Closeness implies a metric, which for the moment we assume is Euclidean distance. So, in words, we find the k observations with x_i closest to x in input space, and average their responses.

Nearest-Neighbor Methods

原文：https://www.cnblogs.com/donggongdechen/p/10252374.html