Description
This text presents a wide-ranging and rigorous overview of nearest neighbor methods, one of the most important paradigms in machine learning. Now in one self-contained volume, this book systematically covers key statistical, probabilistic, combinatorial and geometric ideas for understanding, analyzing and developing nearest neighbor methods.
Gerard Biau is a professor at Universite Pierre et Marie Curie (Paris). Luc Devroye is a professor at the School of Computer Science at McGill University (Montreal).
Reviews
"This book deals with different aspects regarding this approach, starting with the standard k-nearest neighbor model, and passing through the weighted k-nearest neighbor model, estimations for entropy, regression functions etc. ... It is intended for a large audience, including students, teachers, and researchers." (Florin Gorunescu, zbMATH 1330.68001, 2016)
Book Information
ISBN 9783319253862
Author Gerard Biau
Format Hardback
Page Count 290
Imprint Springer International Publishing AG
Publisher Springer International Publishing AG
