1st ed. 2015, IX, 290 p. 4 illus. in color.
Printed book Hardcover
ISBN 978-3-319-25386-2
▶ 99,99 € | £89.99
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G. Biau, L. Devroye
Lectures on the Nearest Neighbor Method
Series: Springer Series in the Data Sciences
▶ Presents a rigorous overview of nearest neighbor methods
▶ Many different components covered: statistical, probabilistic, combinatorial, and geometric ideas
▶ Extensive appendix material provided
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).
