Data Mining ：Concepts, Models, Methods, and Algorithms

Publication subTitle ：Concepts, Models, Methods, and Algorithms

Author： Mehmed Kantardzic  

Publisher： John Wiley & Sons Inc‎

Publication year： 2011

E-ISBN: 9781118029121

P-ISBN(Hardback):  9780470890455

Subject： TP Automation Technology , Computer Technology;TP39 computer application

Language： ENG

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Description

This book reviews state-of-the-art methodologies and techniques for analyzing enormous quantities of raw data in high-dimensional data spaces, to extract new information for decision making. The goal of this book is to provide a single introductory source, organized in a systematic way, in which we could direct the readers in analysis of large data sets, through the explanation of basic concepts, models and methodologies developed in recent decades.

 

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If you are an instructor or professor and would like to obtain a solutions manual, please send an email to: pressbooks@ieee.org

 

Chapter

CONTENTS

pp.：  1 – 9

PREFACE TO THE SECOND EDITION

pp.：  9 – 15

PREFACE TO THE FIRST EDITION

pp.：  15 – 17

1: DATA-MINING CONCEPTS

pp.：  17 – 21

2: PREPARING THE DATA

pp.：  21 – 46

3: DATA REDUCTION

pp.：  46 – 73

4: LEARNING FROM DATA

pp.：  73 – 107

5: STATISTICAL METHODS

pp.：  107 – 160

6: DECISION TREES AND DECISION RULES

pp.：  160 – 189

7: ARTIFICIAL NEURAL NETWORKS

pp.：  189 – 219

8: ENSEMBLE LEARNING

pp.：  219 – 255

9: CLUSTER ANALYSIS

pp.：  255 – 269

10: ASSOCIATION RULES

pp.：  269 – 300

11: WEB MINING AND TEXT MINING

pp.：  300 – 320

12: ADVANCES IN DATA MINING

pp.：  320 – 348

13: GENETIC ALGORITHMS

pp.：  348 – 405

14: FUZZY SETS AND FUZZY LOGIC

pp.：  405 – 434

15: VISUALIZATION METHODS

pp.：  434 – 467

APPENDIX A

pp.：  467 – 490

APPENDIX B: DATA-MINING APPLICATIONS

pp.：  490 – 516

BIBLIOGRAPHY

pp.：  516 – 530

INDEX

pp.：  530 – 549

LastPages

pp.：  549 – 554

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