Computational Intelligence for Missing Data Imputation, Estimation, and Management: Knowledge Optimization Techniques, 1st Edition

  • Tshilidzi Marwala
  • Published By:
  • ISBN-10: 1605663379
  • ISBN-13: 9781605663371
  • Grade Level Range: College Freshman - College Senior
  • 306 Pages | eBook
  • Original Copyright 2009 | Published/Released July 2009
  • This publication's content originally published in print form: 2009

  • Price:  Sign in for price

About

Overview

Focuses on methods to estimate missing values given to observed data. Presents current and new computational intelligence techniques that allow computers to learn the underlying structure of data.

Table of Contents

Front Cover.
Title Page.
Copyright Page.
Table of Contents.
Nomenclature.
Foreword.
Preface.
Acknowledgment.
1: Introduction to Missing Data.
2: Estimation of Missing Data Using Neural Networks and Genetic Algorithms.
3: A Hybrid Approach to Missing Data: Bayesian Neural Networks, Principal Component Analysis and Genetic Algorithms.
4: Maximum Expectation Algorithms for Missing Data Estimation.
5: Missing Data Estimation Using Rough Sets.
6: Support Vector Regression for Missing Data Estimation.
7: Committee of Networks for Estimating Missing Data.
8: Online Approaches to Missing Data Estimation.
9: Missing Data Approaches to Classification.
10: Optimization Methods for Estimation of Missing Data.
11: Estimation of Missing Data Using Neural Networks and Decision Trees.
12: Control of Biomedical System Using Missing Data Approaches.
13: Emerging Missing Data Estimation Problems: Heteroskedasticity; Dynamic Programming and Impact of Missing Data.
About the Author.
Index.