Online Courses to Learn K-Nearest Neighbors

Explore 2 data science courses and free resources covering everything you need to know about K-Nearest Neighbors.

Overview

In statistics, the k-nearest neighbors algorithm (k-NN) is a non-parametric classification method first developed by Evelyn Fix and Joseph Hodges in 1951, and later expanded by Thomas Cover. It is used for classification and regression. In both cases, the input consists of the k closest training examples in data set.

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Career Relevance

K-Nearest Neighbors is most likely to appear on Data Scientist job descriptions where we found it mentioned 0.2 percent of the time.

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