Lectures on the Nearest Neighbor Method
Gérard Biau author Luc Devroye author
Format:Paperback
Publisher:Springer International Publishing AG
Published:21st Mar '19
Currently unavailable, and unfortunately no date known when it will be back
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.
Gérard Biau is a professor at Université Pierre et Marie Curie (Paris). Luc Devroye is a professor at the School of Computer Science at McGill University (Montreal).
“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)
ISBN: 9783319797823
Dimensions: unknown
Weight: unknown
290 pages
Softcover reprint of the original 1st ed. 2015