Authors:
- 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)
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Front Matter
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Support Vector Machines: Theory and Algorithms
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Front Matter
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Part I
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Multiple Criteria Programming: Theory and Algorithms
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Front Matter
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Applications in Various Fields
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Front Matter
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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
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, Research Cntr on Fict. Econ. & Data Sci., Chinese Academy of Sciences, Beijing, China, People's Republic
Yong Shi, Yingjie Tian
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, School of Management and Economics, University of Electr. Science & Technol., Chengdu, China, People's Republic
Gang Kou
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, School of Managment and Economics, University of Electr. Science & Technol., Chengdu, China, People's Republic
Yi Peng
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, Institute of Policy and Management, Chinese Academy of Sciences, Beijing, China, People's Republic
Jianping Li
Bibliographic Information
Book Title: Optimization Based Data Mining: Theory and Applications
Authors: Yong Shi, Yingjie Tian, Gang Kou, Yi Peng, Jianping Li
Series Title: Advanced Information and Knowledge Processing
DOI: https://doi.org/10.1007/978-0-85729-504-0
Publisher: Springer London
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag London Limited 2011
Hardcover ISBN: 978-0-85729-503-3Published: 18 May 2011
Softcover ISBN: 978-1-4471-2653-9Published: 12 July 2013
eBook ISBN: 978-0-85729-504-0Published: 16 May 2011
Series ISSN: 1610-3947
Series E-ISSN: 2197-8441
Edition Number: 1
Number of Pages: XVI, 316
Topics: Data Mining and Knowledge Discovery, Input/Output and Data Communications