K-Nearest Neighbor(KNN) Algorithm in Machine Learning

The K-Nearest Neighbors (KNN) algorithm is a supervised machine learning method used for classification and regression tasks. Developed in 1951 by Evelyn Fix and Joseph Hodges, and later expanded by Thomas Cover, KNN is widely used for pattern recognition, data mining, and intrusion detection. KNN is a non-parametric algorithm, meaning it does not assume any underlying data distribution. The algorithm classifies data points based on their proximity to other data points in a training set. This article delves into the fundamentals, workings, and implementation of the KNN algorithm.

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