Nearest Neighbour

Nearest neighbor (NN) methods are a cornerstone of machine learning, aiming to classify data points based on their proximity to labeled examples in a feature space. Current research focuses on enhancing NN's performance through variations like fuzzy and fuzzy-rough NN, exploring optimal weighting schemes and distance metrics, and integrating NN into ensemble methods and contextual bandit settings. These advancements improve accuracy and efficiency, particularly in applications such as image recognition, text classification, and audio analysis, demonstrating NN's continued relevance across diverse domains.