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Nearest‐neighbor methods

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Abstract Nearest‐neighbor classification is a simple and popular method for supervised classification. The basic method is to classify a query point as being of a certain class if of the k‐nearest neighbors of the query point, more of them belong to this class than to any other class. Variations of the basic method include weighted nearest‐neighbor methods and adaptive nearest‐neighbor methods (which allow some variables to have greater influence than other variables). WIREs Comput Stat 2012, 4:307–309. doi: 10.1002/wics.1195 This article is categorized under: Statistical Learning and Exploratory Methods of the Data Sciences > Clustering and Classification Statistical Learning and Exploratory Methods of the Data Sciences > Pattern Recognition

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Statistical Learning and Exploratory Methods of the Data Sciences > Pattern Recognition
Statistical Learning and Exploratory Methods of the Data Sciences > Clustering and Classification

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