Optimization Based Data Mining: Theory and Applications (Advanced Information and Knowledge Processing)

Optimization techniques have been widely adopted to implement various data mining algorithms. In addition to well-known Support Vector Machines (SVMs) (which are based on quadratic programming), different versions of Multiple Criteria Programming (MCP) have been extensively used in data separations. Since optimization based data mining methods differ from statistics, decision tree induction, and neural networks, their theoretical inspiration has attracted many researchers who are interested in algorithm development of data mining. __Optimization based Data Mining: Theory and Applications__, mainly focuses on MCP and SVM especially their recent theoretical progress and real-life applications in various fields. These include finance, web services, bio-informatics and petroleum engineering, which has triggered the interest of practitioners who look for new methods to improve the results of data mining for knowledge discovery. Most of the material in this book is directly from the research and application activities that the authors’ research group has conducted over the last ten years. Aimed at practitioners and graduates who have a fundamental knowledge in data mining, it demonstrates the basic concepts and foundations on how to use optimization techniques to deal with data mining problems. Front Matter....Pages I-XV Front Matter....Pages 1-1 Support Vector Machines for Classification Problems....Pages 3-13 LOO Bounds for Support Vector Machines....Pages 15-46 Support Vector Machines for Multi-class Classification Problems....Pages 47-60 Unsupervised and Semi-supervised Support Vector Machines....Pages 61-79 Robust Support Vector Machines....Pages 81-105 Feature Selection via l p -Norm Support Vector Machines....Pages 107-116 Front Matter....Pages 117-117 Multiple Criteria Linear Programming....Pages 119-132 MCLP Extensions....Pages 133-156 Multiple Criteria Quadratic Programming....Pages 157-170 Non-additive MCLP....Pages 171-181 MC2LP....Pages 183-192 Front Matter....Pages 193-193 Firm Financial Analysis....Pages 195-201 Personal Credit Management....Pages 203-231 Health Insurance Fraud Detection....Pages 233-235 Network Intrusion Detection....Pages 237-241 Internet Service Analysis....Pages 243-248 HIV-1 Informatics....Pages 249-258 Anti-gen and Anti-body Informatics....Pages 259-267 Geochemical Analyses....Pages 269-275 Intelligent Knowledge Management....Pages 277-293 Back Matter....Pages 295-316 Optimization techniques have been widely adopted to implement various data mining algorithms. This book focuses on cutting-edge theoretical developments and real-life applications in optimization, covering a range of fields from finance to bioinformatics. Pt. 1. Support vector machines : theory and algorithms pt. 2. Multiple criteria programming : theory and algorithms pt. 3. Application in various fields. By Yong Shi, Yingjie Tian, Gang Kou, Yi Peng, Jianping Li.