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k-Nearest Neighbor Learning Explained by Deekshith Reddy Kotla is a document available to read on EtoBox.

The document discusses k-nearest neighbor (k-NN) learning, an instance-based learning algorithm. It describes how k-NN works by finding the k closest training instances to make predictions, defines distance metrics, and how it can be used for both discrete and continuous valued prediction problems. It also introduces variants like distance weighting and addressing issues like the curse of dimensionality.

Author
Deekshith Reddy Kotla
Language
EN