Machine Learning a Concise Introduction - Steven Knox (2018).pdf

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Machine Learning:
a Concise Introduction
WILEY SERIES IN PROBABILITY AND STATISTICS
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Machine Learning:
a Concise Introduction
Steven W. Knox
This edition first published 2018
This work is a U.S. Government work and is in the public domain in the U.S.A.
Published 2018 by John Wiley & Sons, Inc
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Library of Congress Cataloging-in-Publication Data
Names: Knox, Steven W., author.
Title: Machine learning : a concise introduction / by Steven W. Knox.
Description: Hoboken, New Jersey : John Wiley & Sons, 2018. | Series: Wiley series in probability and
statistics |
Identifiers: LCCN 2017058505 (print) | LCCN 2018004509 (ebook) | ISBN 9781119439073 (pdf) |
ISBN 9781119438984 (epub) | ISBN 9781119439196 (cloth)
Subjects: LCSH: Machine learning.
Classification: LCC Q325.5 (ebook) | LCC Q325.5 .K568 2018 (print) | DDC 006.3/1–dc23
LC record available at https://lccn.loc.gov/2017058505
Cover image: © Verticalarray/Shutterstock
Cover design by Wiley
Set in 10/12pt TimesStd by Aptara Inc., New Delhi, India
10 9 8 7 6 5 4 3 2 1
Contents
Preface
Organization—How to Use This Book
Acknowledgments
About the Companion Website
1
2
Introduction—Examples from Real Life
The Problem of Learning
2.1 Domain
2.2 Range
2.3 Data
2.4 Loss
2.5
Risk
2.6 The Reality of the Unknown Function
2.7 Training and Selection of Models, and Purposes of Learning
2.8 Notation
Regression
3.1 General Framework
3.2 Loss
3.3 Estimating the Model Parameters
3.4 Properties of Fitted Values
3.5 Estimating the Variance
3.6
A Normality Assumption
3.7 Computation
3.8 Categorical Features
3.9 Feature Transformations, Expansions, and Interactions
3.10 Variations in Linear Regression
3.11 Nonparametric Regression
xi
xiii
xvii
xix
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3
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4
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8
12
12
13
15
16
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25
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32
3

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