k-Nearest Neighbors Classification

The k-nearest neighbors (k-NN) classification is a method of classification that uses a training set chosen from the data as a point of reference in classifying observations. The idea of the method is to find the k elements of the training set that are closest to the target element to be classified. The target is then classified as belonging to whatever category is the most frequent among the k-objects.