Carregant...
Carregant...

Vés al contingut (premeu Retorn)

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
Document cientificotècnic
Data
2013
Codi
LSI-13-2-R
Repositori
http://hdl.handle.net/2117/96707 Obrir en finestra nova
Resum
In this work a new way to calculate the multivariate joint entropy is presented. This measure is the basis for a fast information-theoretic based evaluation of gene relevance in a Microarray Gene Expression data context. Its low complexity is based on the reuse of previous computations to calculate current feature relevance. The mu-TAFS algorithm --named as such to differentiate it from previous TAFS algorithms-- implements a simulated annealing technique specially designed for feature subset se...
Citació
González, F.F., Belanche, Ll. "Feature selection for microarray gene expression data using simulated annealing guided by the multivariate joint entropy". 2013.
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

Arxius