Computational Intelligence for Missing Data Imputation, Estimation, and Management: Knowledge Optimization Techniques: 9781605663364: Computer Science & IT Books

Publication Status: E-Book and Print Version Available for Purchase

ISBN13: 9781605663364

EISBN13: 9781605663371

DOI: 10.4018/978-1-60566-336-4

Description:

The issue of missing data imputation has been extensively explored in information engineering, though needing a new focus and approach in research.

Computational Intelligence for Missing Data Imputation, Estimation, and Management: Knowledge Optimization Techniques focuses on methods to estimate missing values given to observed data. Providing a defining body of research valuable to those involved in the field of study, this book presents current and new computational intelligence techniques that allow computers to learn the underlying structure of data.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

Artificial Neural Networks
Hybrid approach to missing data
Introduction of missing data
Maximum likelihood approach
Missing data estimation approaches
Missing data estimation method
Missing data estimation methodology
Missing data imputation
Missing data mechanism
Missing data patterns
Optimization Techniques

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Reviews

This book is carefully written to give a good balance between theory and application of various missing data estimation techniques.

– Tshilidzi Marwala, University of Witwatersrand, South Africa

An opening discussion of traditional missing data issues is followed by chapters covering a range of computational intelligence.

– Book News Inc. (June 2009)

Paradoxically, in these days of information glut, there is a concurrent problem of data loss--missing and incomplete data. Statisticians have generated a wealth of knowledge on the methods of handling missing data. While solving differential equations, it is common to encounter such problems as missing initial conditions, missing boundary conditions, and unspecified location of the boundary contour. Such inverse problems, said to be improperly posed, are often solved by regularization--a method of systematically guessing the missing values. [...] A decent attempt at assembling the available tools under one cover.

– Rao Vemur, Computing Reviews

Tshilidzi Marwala holds a Chair of Systems Engineering at the School of Electrical and Information Engineering at the University of the Witwatersrand. He is the youngest recipient of the Order of Mapungubwe (whose other recipients are Nobel Prize Winners Sydney Brenner and J.M. Coetzee) and was awarded the President Award by the National Research Foundation. He holds a Bachelor of Science in Mechanical Engineering (Magna Cum Laude) from Case Western Reserve University, a Master of Engineering from the University of Pretoria, PhD in Engineering from University of Cambridge (St John's College) and attended a Program for Leadership Development at Harvard Business School. He was a post-doctoral research associate at the Imperial College of Science, Technology and Medicine and in year 2006 to 2007 was a visiting fellow at Harvard University. His research interests include theory and application of computational intelligence to engineering, computer science, finance, social science and medicine. He has published over 150 papers in journals, proceedings and book chapters and has supervised 30 master and PhD theses. His book Computational Intelligence for Modelling Complex Systems is published by Research India Publications. He is the Associate Editor of the International Journal of Systems Science. His work has appeared in publications such as the New Scientist and Time Magazine. He was a Chair of the Local Loop Unbundling Committee, is a Deputy Chair of the Limpopo Business Support Agency and has been on boards of EOH (Pty) Ltd, City Power (Pty) Ltd, State Information Technology Agency (Pty) Ltd, Statistics South Africa and the National Advisory Council on Innovation. He is a trustee of the Bradlow Foundation as well as the Carl and Emily Fuchs Foundation. He is a Senior Member of the IEEE and a member of the ACM.

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