The Handbook of Data Mining

by Nong Ye (Editor)

Overview

Authored by international researchers in academia and industry, 28 contributions aim to present a comprehensive treatment of the methodologies, management, and applications of data mining. Each concept or tool is illustrated by simple examples and real-world applications. A sampling of topics includes Bayesian data analysis, security issues, and performance analysis and evaluation. Some of the applications described include the mining of human performance data, geospatial data, and manufacturing quality data. Editor Ye teaches industrial engineering at Arizona State University. Annotation (c)2003 Book News, Inc., Portland, OR

Product Details

ISBN-13:	9781410607515
Publisher:	CRC Press
Publication date:	04/01/2003
Sold by:	Barnes & Noble
Format:	eBook
Pages:	720
File size:	12 MB
Note:	This product may take a few minutes to download.

About the Author

Nong Ye

Table of Contents

Contents: G. Salvendy, Foreword. N. Ye, Preface. Part I:Methodologies of Data Mining. J. Gehrke, Decision Trees. G.I. Webb, Association Rules. J. Si, B.J. Nelson, G.C. Runger, Artificial Neural Network Models for Data Mining. C.M. Borror, Statistical Analysis of Normal and Abnormal Data. D. Madigan, G. Ridgeway, Bayesian Data Analysis. S.L. Scott, Hidden Markov Processes and Sequential Pattern Mining. G. Ridgeway, Strategies and Methods for Prediction. D.W. Apley, Principal Components and Factor Analysis. E. Ip, I. Cadez, P. Smyth, Psychometric Methods of Latent Variable Modeling. J. Ghosh, Scalable Clustering. G. Das, D. Gunopulos, Time Series Similarity and Indexing. Y-C. Lai, Z. Liu, N. Ye, T. Yalcinkaya, Nonlinear Time Series Analysis. B-H. Park, H. Kargupta, Distributed Data Mining. Part II:Management of Data Mining. D. Pyle, Data Collection, Preparation, Quality, and Visualization. T. Wu, X. Li, Data Storage and Management. H. Liu, L. Yu, H. Motoda, Feature Extraction, Selection, and Construction. S.M. Weiss, T. Zhang, Performance Analysis and Evaluation. C. Clifton, Security and Privacy. R. Grossman, M. Hornick, G. Meyer, Emerging Standards and Interfaces. Part III:Applications of Data Mining. D.A. Nembhard, Mining Human Performance Data. R. Feldman, Mining Text Data. S. Shekhar, R.R. Vatsavai, Mining Geospatial Data. C. Kamath, Mining Science and Engineering Data. M.J. Zaki, Mining Data in Bioinformatics. R. Cooley, Mining Customer Relationship Management (CRM) Data. N. Ye, Mining Computer and Network Security Data. C. Djeraba, G. Fernandez, Mining Image Data. M.C. Testik, G.C. Runger, Mining Manufacturing Quality Data.

Editorial Reviews

"...a useful resource for anyone new to data mining, and for anyone wishing to discover what potential tools are available, as well as what might be achieved through the use of those tools...a good 'data-mining handbook' to have on one's shelves."
—Short Book Reviews

"This handbook will be a valuable reference in the library of the human factors analyst with advanced statistical and analytic skills. The coverage is comprehensive and state-of-the-art by leading experts in data mining. The handbook is a tool kit to be consulted and referenced in the decision to conduct and plan a data-mining effort."
—Ergonomics in Design

"This collection of essays contains chapters on many of the common techniques, problems, and applications associated with data mining....overall this book is an excellent reference for practitioners who need a practical introduction to topics in data mining."

—Journal of the American Statistical Association

From the Publisher