Nearest-Neighbor Methods: A Modern Perspective

Aryeh Kontorovich () and Samory Kpotufe
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Aryeh Kontorovich: Ben-Gurion University, Department of Computer Science
Samory Kpotufe: Columbia University, Department of Statistics

A chapter in Machine Learning for Data Science Handbook, 2023, pp 75-92 from Springer

Abstract: Abstract This chapter aims at providing an overview of various modern approaches to learning with nearest neighbors in general metric spaces. We provide the necessary background and then proceed to cover classification, regression—with sufficient detail and literature pointers to yield practical insights into how various configuration and pre-processing choices, e.g., metric, the number of neighbors, data subsampling, and compression, affect learning and computational performance.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-24628-9_5

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DOI: 10.1007/978-3-031-24628-9_5

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