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Computational Intelligence for Missing Data Imputation, Estimation, and Management—Knowledge Optimization Techniques

Computational Intelligence for Missing Data Imputation, Estimation, and Management: Knowledge Optimization Techniques

by Tshilidzi Marwala (ed)

2009 (326 pages)

ISBN:9781605663364

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.

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Computational Intelligence for Missing Data Imputation, Estimation, and Management—Knowledge Optimization Techniques
Nomenclature
Foreword
Preface
Chapter I	-	Introduction to Missing Data
Chapter II	-	Estimation of Missing Data Using Neural Networks and Genetic Algorithms
Chapter III	-	A Hybrid Approach to Missing Data: Bayesian Neural Networks, Principal Component Analysis and Genetic Algorithms
Chapter IV	-	Maximum Expectation Algorithms for Missing Data Estimation
Chapter V	-	Missing Data Estimation Using Rough Sets
Chapter VI	-	Support Vector Regression for Missing Data Estimation
Chapter VII	-	Committee of Networks for Estimating Missing Data
Chapter VIII	-	Online Approaches to Missing Data Estimation
Chapter IX	-	Missing Data Approaches to Classification
Chapter X	-	Optimization Methods for Estimation of Missing Data
Chapter XI	-	Estimation of Missing Data Using Neural Networks and Decision Trees
Chapter XII	-	Control of Biomedical System Using Missing Data Approaches
Chapter XIII	-	Emerging Missing Data Estimation Problems: Heteroskedasticity; Dynamic Programming and Impact of Missing Data