CINECA IRIS Institutional Research Information System
IRIS è l’archivio della produzione scientifica della Fondazione Bruno Kessler.
EnglishWe describe a new wrapper algorithm for fast feature ranking in classification problems. The E-RFE (Entropy-based Recursive Feature Elimination) method eliminates chunks of uninteresting features according to the entropy of the weights distribution of a SVM classifier. With specific regard to DNA microarray datasets, the method is designed to support computationally intensive model selection in classification problems in which the number of features is much larger than the number of samples. We test E-RFE on synthetic and real data sets, comparing it with other SVM-based methods. The speed-up obtained with E-RFE supports predictive modeling on high dimensional microarray data
Scheda prodotto non validato
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte di FBK.
| Titolo: | An accelerated procedure for recursive feature ranking on microarray data | |
| Autori: | ||
| Data di pubblicazione: | 2003 | |
| Abstract: | We describe a new wrapper algorithm for fast feature ranking in classification problems. The E-RFE (Entropy-based Recursive Feature Elimination) method eliminates chunks of uninteresting features according to the entropy of the weights distribution of a SVM classifier. With specific regard to DNA microarray datasets, the method is designed to support computationally intensive model selection in classification problems in which the number of features is much larger than the number of samples. We test E-RFE on synthetic and real data sets, comparing it with other SVM-based methods. The speed-up obtained with E-RFE supports predictive modeling on high dimensional microarray data | |
| Handle: | http://hdl.handle.net/11582/2085 | |
| ISBN: | 9780080443201 | |
| Appare nelle tipologie: | 2.1 Contributo in volume (Capitolo o Saggio) |
File in questo prodotto:
http://hdl.handle.net/11582/2085
Copyright © 2021