Nearest Neighbors for Classification - KDnuggets

K-nearest neighbors (KNN) is a type of supervised learning machine learning algorithm and is used for both regression and classification tasks. KNN is used to make predictions on the test data set based on the characteristics of the current training data points. This is done by calculating the distance between the test data and training data, assuming that similar things exist within close proximity. The algorithm will have stored learned data, making it more effective at predicting and categorising new data points. When a new data point is inputted, the KNN algorithm will learn its characteristics/features.