Abstract

Classifier combination is a powerful paradigm to deal with difficult pattern classification problems. As matter of this fact, multi-classifier systems have been widely adopted in many applications for which very high classification performance is necessary. Notwithstanding, multi-classifier system design is still an open problem. In fact, complexity of multi-classifiers systems make the theoretical evaluation of system performance very difficult and, consequently, also the design of a multi-classifier system. This paper presents a new approach for the design of a multi-classifier system. In particular, the problem of feature selection for a multiclassifier system is addressed and a genetic algorithm is proposed for automatic selecting the optimal set of features for each individual classifier of the multi-classifier system. The experimental results, carried out in the field of handwritten digit recognition, demonstrate the effectiveness of the proposed approach.

Autore Pugliese

• Impedovo Donato , Pirlo Giuseppe

Tutti gli autori

• IMPEDOVO D.;PIRLO G.

Titolo volume/Rivista

Non Disponibile

Anno di pubblicazione

2012

ISSN

Non Disponibile

ISBN

978-0-7695-4774-9

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

Non Disponibile

Numero di citazioni Scopus

2

Ultimo Aggiornamento Citazioni

Non Disponibile

Settori ERC

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Codici ASJC

Non Disponibile