Missing data imputation in multivariate data by evolutionary algorithms

Thumbnail
Enlaces del Item
URI: http://hdl.handle.net/10818/36915
Visitar enlace: https://www.sciencedirect.com/ ...
ISSN: 0747-5632
DOI: 10.1016/j.chb.2010.06.026
Estadísticas
Ver Estadísticas de uso
Métricas
Catalogación bibliográfica
Mostrar el registro completo del ítem
Autor/es
Figueroa García, Juan Carlos; Kalenatic, Dusko; López Bello, Cesar Amilcar
Fecha
2011-09
Resumen
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.
Palabras clave
Ubicación
Computers in Human Behavior Volume 27, Issue 5, September 2011, Pages 1468-1474
Colecciones a las que pertenece
Attribution-NonCommercial-NoDerivatives 4.0 InternationalExcepto si se señala otra cosa, la licencia del ítem se describe como Attribution-NonCommercial-NoDerivatives 4.0 International