Myatt - Making Sense of Data II - Practical Guide to Data Visualization (Wiley, 2009).pdf

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MAKING SENSE OF
DATA II
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MAKING SENSE OF
DATA II
A Practical Guide to Data Visualization,
Advanced Data Mining Methods, and
Applications
GLENN J. MYATT
WAYNE P. JOHNSON
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Copyright # 2009 by John Wiley & Sons, Inc. All rights reserved.
Published by John Wiley & Sons, Inc., Hoboken, New Jersey
Published simultaneously in Canada
No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or
by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as
permitted under Sections 107 or 108 of the 1976 United States Copyright Act, without either the prior
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Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) 750-8400, fax (978)
750-4470, or on the web at www.copyright.com. Requests to the Publisher for permission should be
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(201) 748-6011, fax (201) 748-6008, or online at http://www.wiley.com/go/permission.
Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts
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Library of Congress Cataloging-in-Publication Data:
Myatt, Glenn J., 1969-
Making sense of data II: a practical guide to data visualization, advanced data mining methods, and
applications/Glenn J. Myatt, Wayne P. Johnson.
p. cm.
Making sense of data 2
Includes bibliographical references and index.
ISBN 978-0-470-22280-5 (pbk.)
1. Data mining. 2. Information visualization. I. Johnson, Wayne P. II.
Title. III. Title: Making sense of data 2.
QA76.9.D343M93 2008
005.74- -dc22
2008024103
Printed in the United States of America
0987654321
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CONTENTS
PREFACE
xi
1 INTRODUCTION
1
1.1 Overview
1
1.2 Definition
1
1.3 Preparation
2
1.3.1 Overview
2
1.3.2 Accessing Tabular Data
3
1.3.3 Accessing Unstructured Data
3
1.3.4 Understanding the Variables and Observations
3
1.3.5 Data Cleaning
6
1.3.6 Transformation
7
1.3.7 Variable Reduction
9
1.3.8 Segmentation
10
1.3.9 Preparing Data to Apply
10
1.4 Analysis
11
1.4.1 Data Mining Tasks
11
1.4.2 Optimization
12
1.4.3 Evaluation
12
1.4.4 Model Forensics
13
1.5 Deployment
13
1.6 Outline of Book
14
1.6.1 Overview
14
1.6.2 Data Visualization
14
1.6.3 Clustering
15
1.6.4 Predictive Analytics
15
1.6.5 Applications
16
1.6.6 Software
16
1.7 Summary
16
1.8 Further Reading
17
2 DATA VISUALIZATION
19
2.1 Overview
19
2.2 Visualization Design Principles
20
2.2.1 General Principles
20
2.2.2 Graphics Design
23
2.2.3 Anatomy of a Graph
28
v
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