Computational Intelligence for Missing Data Imputation, Estimation, and Management - Marwala, Tshilidzi

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Résumé :
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.

Biographie:
PROFESSOR TSHILIDZI MARWALA is the vice-chancellor and principal of the University of Johannesburg. A professor of Electrical Engineering, Marwala is a leading thinker in artificial intelligence and was the chair of System Engineering at the University of the Witwatersrand. A respected academic and author, Marwala has served as a trustee of the Nelson Mandela Foundation and as a councillor at the National Advisory Council on Innovation. He is now deputy to President Cyril Ramaphosa on the South African Presidential Commission on the Fourth Industrial Revolution.

Sommaire:
Artificial neural networks; Hybrid approach to missing data; Introduction of missing data; Maximum likelihood approach; Missing data estimation approaches; Missing data imputation; Missing data patterns; Missing data mechanism; Missing data estimation methodology; Optimization techniques.