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Optimization Based Data Mining: Theory and Applications

  • Book
  • © 2011

Overview

  • Introduces MCLP for data mining intuitively, systemically and comprehensively
  • Offers classification problems and regression problems which are the two main components of data mining
  • Constructs SVM's for solving multi-class classification problems
  • Includes supplementary material: sn.pub/extras

Part of the book series: Advanced Information and Knowledge Processing (AI&KP)

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Table of contents (20 chapters)

  1. Support Vector Machines: Theory and Algorithms

  2. Part I

  3. Multiple Criteria Programming: Theory and Algorithms

  4. Part II

  5. Applications in Various Fields

  6. Part III

Keywords

About this book

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.

Authors and Affiliations

  • , Research Cntr on Fict. Econ. & Data Sci., Chinese Academy of Sciences, Beijing, China, People's Republic

    Yong Shi, Yingjie Tian

  • , School of Management and Economics, University of Electr. Science & Technol., Chengdu, China, People's Republic

    Gang Kou

  • , School of Managment and Economics, University of Electr. Science & Technol., Chengdu, China, People's Republic

    Yi Peng

  • , Institute of Policy and Management, Chinese Academy of Sciences, Beijing, China, People's Republic

    Jianping Li

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