K-nearest Neighbors in Scikit-learn - KDnuggets

K-nearest neighbors (KNN) is a type of supervised learning machine learning algorithm and can be used for both regression and classification tasks. A supervised machine learning algorithm is dependent on labeled input data which the algorithm learns on and uses its learnt knowledge to produce accurate outputs when unlabeled data is inputted. The use of KNN is to make predictions on the test data set based on the characteristics (labeled data) of the training data. The method used to make these predictions is by calculating the distance between the test data and training data, assuming that similar characteristics or attributes of the data points exist within close proximity. It allows us to identify and assign the category of the new data whilst taking into consideration its characteristics based on learned data points from the training data.