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Feature set enhancement via hierarchical clustering for microarray classification

Autor
Bosio, M.; Bellot, P.; Salembier, P.; Oliveras, A.
Tipus d'activitat
Presentació treball a congrés
Nom de l'edició
GENSIPS 2011 - IEEE International Workshop on Genomic Signal Processing and Statistics
Any de l'edició
2011
Data de presentació
2011
Llibre d'actes
Proceedings - IEEE International Workshop on Genomic Signal Processing and Statistics
Pàgina inicial
226
Pàgina final
229
Repositori
http://hdl.handle.net/2117/87114 Obrir en finestra nova
Resum
A new method for gene expression classification is proposed in this paper. In a first step, the original feature set is enriched by including new features, called metagenes, produced via hierarchical clustering. In a second step, a reliable classifier is built from a wrapper feature selection process. The selection relies on two criteria: the classical classification error rate and a new reliability measure. As a result, a classifier with good predictive ability using as few features as possible...
Citació
Bosio, M., Bellot, P., Salembier, P., Oliveras, A. Feature set enhancement via hierarchical clustering for microarray classification. A: IEEE International Workshop on Genomic Signal Processing and Statistics. "Proceedings - IEEE International Workshop on Genomic Signal Processing and Statistics". 2011, p. 226-229.
Paraules clau
Cancer microarray classification, Feature selection, Hierarchical clustering, Treelet
Grup de recerca
GPI - Grup de Processament d'Imatge i Vídeo
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center

Participants