Authors:
- Summarizes the latest applications of robust optimization in data mining
- An essential accompaniment for theoreticians and data miners
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Optimization (BRIEFSOPTI)
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Table of contents (6 chapters)
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Front Matter
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Back Matter
About this book
Data uncertainty is a concept closely related with most real life applications that involve data collection and interpretation. Examples can be found in data acquired with biomedical instruments or other experimental techniques. Integration of robust optimization in the existing data mining techniques aim to create new algorithms resilient to error and noise.
This work encapsulates all the latest applications of robust optimization in data mining. This brief contains an overview of the rapidly growing field of robust data mining research field and presents the most well known machine learning algorithms, their robust counterpart formulations and algorithms for attacking these problems.
This brief will appeal to theoreticians and data miners working in this field.
Reviews
From the reviews:
“The goal of the book is to provide a guide for junior researchers interested in pursuing theoretical research in data mining and robust optimization and has been developed so that each chapter can be studied independent of the others.” (Hans Benker, Zentralblatt MATH, Vol. 1260, 2013)Authors and Affiliations
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, Department of Industrial Engineering, University of Central Florida, Orlando, USA
Petros Xanthopoulos
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, Department of Industrial & Systems Engin, University of Florida, Gainesville, USA
Panos M. Pardalos
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, Industrial Engineering, University of Ocklahoma, Norman, USA
Theodore B. Trafalis
Bibliographic Information
Book Title: Robust Data Mining
Authors: Petros Xanthopoulos, Panos M. Pardalos, Theodore B. Trafalis
Series Title: SpringerBriefs in Optimization
DOI: https://doi.org/10.1007/978-1-4419-9878-1
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Petros Xanthopoulos,Panos M. Pardalos,Theodore B. Trafalis 2013
Softcover ISBN: 978-1-4419-9877-4Published: 21 November 2012
eBook ISBN: 978-1-4419-9878-1Published: 28 November 2012
Series ISSN: 2190-8354
Series E-ISSN: 2191-575X
Edition Number: 1
Number of Pages: XII, 59
Number of Illustrations: 6 b/w illustrations
Topics: Optimization, Data Mining and Knowledge Discovery, Software Engineering/Programming and Operating Systems