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k-Nearest Neighbors Classification

k-Nearest Neighbors Classification

k-Nearest Neighbors Classification:

The k-nearest neighbors (k-NN) classification is a method of classification that uses a training set chosen from the data as a point of reference in classifying observations. The idea of the method is to find the k elements of the training set that are closest to the target element to be classified. The target is then classified as belonging to whatever category is the most frequent among the k-objects.

See also: the chapter from XLMiner help

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Courses Using This Term

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Cluster Analysis
This course will teach you how to use various cluster analysis methods to identify possible clusters in multivariate data. Methods discussed include hierarchical clustering, k-means clustering, two-step clustering, and normal mixture models for continuous variables.
Multivariate Statistics
This course will teach you key multivariate procedures such as multivariate analysis of variance (MANOVA), principal components, factor analysis, and classification.
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