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Lectures on the Nearest Neighbor Method Gerard Biau

Lectures on the Nearest Neighbor Method By Gerard Biau

Lectures on the Nearest Neighbor Method by Gerard Biau


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Summary

This text presents a wide-ranging and rigorous overview of nearest neighbor methods, one of the most important paradigms in machine learning.

Lectures on the Nearest Neighbor Method Summary

Lectures on the Nearest Neighbor Method by Gerard Biau

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).

Lectures on the Nearest Neighbor Method 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)

Table of Contents

Part I: Density Estimation.- Order Statistics and Nearest Neighbors.- The Expected Nearest Neighbor Distance.- The k-nearest Neighbor Density Estimate.- Uniform Consistency.- Weighted k-nearest neighbor density estimates.-Local Behavior.- Entropy Estimation.- Part II: Regression Estimation.- The Nearest Neighbor Regression Function Estimate.- The 1-nearest Neighbor Regression Function Estimate.- LP-consistency and Stone's Theorem.- Pointwise Consistency.- Uniform Consistency.- Advanced Properties of Uniform Order Statistics.- Rates of Convergence.- Regression: The Noisless Case.- The Choice of a Nearest Neighbor Estimate.- Part III: Supervised Classification.- Basics of Classification.- The 1-nearest Neighbor Classification Rule.- The Nearest Neighbor Classification Rule. Appendix.- Index.

Additional information

NPB9783319253862
9783319253862
3319253867
Lectures on the Nearest Neighbor Method by Gerard Biau
New
Hardback
Springer International Publishing AG
2015-12-15
290
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
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