K-Nearest Neighbors (KNN) is a simple, easy-to-implement supervised machine learning algorithm that can be used for both classification and regression tasks. For classification, the output is a class membership. An object is classified by a majority vote of its neighbors, with the object being assigned to the class most common among its k nearest neighbors (k is a positive integer, typically small). For regression, the output is the property value for the object. This value is the average of the values of its k nearest neighbors.
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