This paper introduces a new classifier, that is based on fuzzy-integration schemes controlled by a genetic optimisation procedure. Two different types of integration are proposed here, and are validated by experiments on real data sets of biological cells. The performance of our classifier is tested against a feed-forward neural network and a Support Vector Machine. Results show the good performance and robustness of the integrated classifier strategies.
Di Gesù, V., Lo Bosco, G. (2005). A Genetic Integrated Fuzzy Classifier. PATTERN RECOGNITION LETTERS, 26(4), 411-420 [10.1016/j.patrec.2004.08.004].
A Genetic Integrated Fuzzy Classifier
DI GESU', Vito;LO BOSCO, Giosue'
2005-01-01
Abstract
This paper introduces a new classifier, that is based on fuzzy-integration schemes controlled by a genetic optimisation procedure. Two different types of integration are proposed here, and are validated by experiments on real data sets of biological cells. The performance of our classifier is tested against a feed-forward neural network and a Support Vector Machine. Results show the good performance and robustness of the integrated classifier strategies.
File in questo prodotto:
| File | Dimensione | Formato | |
|---|---|---|---|
|
Di Gesù, Lo Bosco - 2005 - A genetic integrated fuzzy classifier.pdf
Solo gestori archvio
Dimensione
315 kB
Formato
Adobe PDF
|
315 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
