Missing data imputation in multivariate data by evolutionary algorithms

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URI: http://hdl.handle.net/10818/36915
Visitar enlace: https://www.sciencedirect.com/ ...
ISSN: 0747-5632
DOI: 10.1016/j.chb.2010.06.026
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Author
Figueroa García, Juan Carlos; Kalenatic, Dusko; López Bello, Cesar Amilcar
Date
2011-09
Abstract
This paper presents a proposal based on an evolutionary algorithm to impute missing observations in multivariate data. A genetic algorithm based on the minimization of an error function derived from their covariance matrix and vector of means is presented. All methodological aspects of the genetic structure are presented. An extended explanation of the design of the fitness function is provided. An application example is solved by the proposed method.
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Ubication
Computers in Human Behavior Volume 27, Issue 5, September 2011, Pages 1468-1474
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