INSEAD Library

Includes bibliographical references and index

Digitized

Data Mining Methods and Applications Contents Preface........................................................................................................................................ xi About the Editors...................................................................................................................... xv Editors and Contributors.......................................................................................................... xix SECTION I TECHNIQUES OF DATA MINING 1 An Approach to Analyzing and Modeling Systems for Real-Time Decisions.................................................................................................... 3 JOHN C. BROCKLEBANK, TOM LEHMAN, TOM GRANT, RICH BURGESS, LOKESH NAGAR, HIMADRI MUKHERJEE, JUEE DADHICH, AND PIAS CHAKLANOBISH 2 Ensemble Strategies for Neural Network Classifiers.............................................................39 PAUL MANGIAMELI AND DAVID WEST 3 Neural Network Classification with Uneven Misclassification Costs and Imbalanced Group Sizes................................................................................. 61 JYHSHYAN LAN, MICHAEL Y. HU, EDDY PATUWO, AND G. PETER ZHANG 4 Data Cleansing with Independent Component Analysis........................................................83 GUANGYIN ZENG AND MARK J. EMBRECHTS 5 A Multiple Criteria Approach to Creating Good Teams over Time ....................................105 RONALD K. KLIMBERG, KEVIN J. BOYLE, AND IRA YERMISH SECTION II APPLICATIONS OF DATA MINING 6 Data Mining Applications in Higher Education.................................................................123 CALI M. DAVIS, J. MICHAEL HARDIN, TOM BOHANNON, AND JERRY OGLESBY 7 Data Mining for Market Segmentation with Market Share Data: A Case Study Approach.............................................................................................. 149 ILLYA MOWERMAN AND SCOTT J. LLOYD 8 An Enhancement of the Pocket Algorithm with Ratchet for Use in Data Mining Applications..................................................... 163 LOUIS W. GLORFELD AND DOUG WHITE 9 Identification and Prediction of Chronic Conditions for Health Plan Members Using Data Mining Techniques......................................... 175 THEODORE L. PERRY, STEPHAN KUDYBA, AND KENNETH D. LAWRENCE 10 Monitoring and Managing Data and Process Quality Using Data Mining: Business Process Management for the Purchasing and Accounts Payable Processes.................................................. 183 DANIEL E. O'LEARY 11 Data Mining for Individual Consumer Models and Personalized Retail Promotions........................................................................................................ 203 RAYID GHANI, CHAD CUMBY, ANDREW FANO, AND MARKO KREMA SECTION III OTHER AREAS OF DATA MINING 12 Data Mining: Common Definitions, Applications, and Misunderstandings................................................................................................ 229 RICHARD D. POLLACK 13 Fuzzy Sets in Data Mining and Ordinal Classification....................................................239 DAVID L. OLSON, HELEN MOSHKOVICH, AND ALEXANDER MECHITOV 14 Developing an Associative Keyword Space of the Data Mining Literature through Latent Semantic Analysis.............................................................................................255 ADRIAN GARDINER 15 A Classification Model for a Two-Class (New Product Purchase) Discrimination Process Using Multiple-Criteria Linear Programming.................................................................................................... 295 KENNETH D. LAWRENCE, DINESH R. PAI, RONALD K. KLIMBERG, STEPHAN KUDYBA, AND SHEILA M. LAWRENCE Index.................................................................................................................................... 305