# K Nearest Neighbors

The *K Nearest Neighbors (KNN)* algorithm is part of a family of *classifier* algorithms that aim to predict the *class* or *category* of an observation. KNN works by calculating the distance, often the Euclidean (i.e., straight line) distance, between observations. In this post, we walk through the application of the KNN algorithm and demonstrate the conditions under which the algorithm excels, does poorly, and is improved through feature engineering.