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Feature selection for microarray gene expression data using simulated annealing guided by the multivariate joint entropy

Autor
González, F.F.; Belanche, Ll.
Tipus d'activitat
Article en revista
Revista
Computación y sistemas
Data de publicació
2014-04-01
Volum
18
Número
2
Pàgina inicial
275
Pàgina final
293
DOI
https://doi.org/10.13053/CyS-18-2-2014-032 Obrir en finestra nova
Projecte finançador
Determinación del origen de la contaminación fecal en el agua
URL
http://cys.cic.ipn.mx/ojs/index.php/CyS/article/view/1473/1885 Obrir en finestra nova
Resum
Microarray classification poses many challenges for data analysis, given that a gene expression data set may consist of dozens of observations with thousands or even tens of thousands of genes. In this context, feature subset selection techniques can be very useful to reduce the representation space to one that is manageable by classification techniques. In this work we use the discretized multivariate joint entropy as the basis for a fast evaluation of gene relevance in a Microarray Gene Expres...
Paraules clau
Feature selection, Microarray gene expression data, Multivariate joint entropy, Simulated annealing
Grup de recerca
IDEAI-UPC Intelligent Data Science and Artificial Intelligence
SOCO - Soft Computing

Participants