Regression is covered elsewhere in the book, but we might also want to run a regression on pockets of the feature space. We can think that our dataset is subject to several data processes. If this is true, only training on similar data points is a good idea.
Using KNN for regression
Getting ready
Our old friend, regression, can be used in the context of clustering. Regression is obviously a supervised technique, so we'll use K-Nearest Neighbors (KNN) clustering rather than k-means. For KNN regression, we'll use the K closest points in the feature space to build the regression rather than using the entire space as in regular regression.
