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In recent years anti-spam filters have become necessary tools for Internet service providers to face up to the continuously growing spam phenomenon. Current server-side anti-spam filters are made up of several modules aimed at detecting different features of spam e-mails. In particular, text categorisation techniques have been investigated by researchers(More)
In the field of pattern recognition, the combination of an ensemble of neural networks has been proposed as an approach to the development of high performance image classification systems. However, previous work clearly showed that such image classification systems are effective only if the neural networks forming them make different errors. Therefore, the(More)
Ensemble methods based on bias–variance analysis Theses Series Abstract Ensembles of classifiers represent one of the main research directions in machine learning. Two main theories are invoked to explain the success of ensemble methods. The first one consider the ensembles in the framework of large margin classifiers, showing that ensembles enlarge the(More)
Multiple classifier systems based on the combination of outputs of a set of different classifiers have been proposed in the field of pattern recognition as a method for the development of high performance classification systems. Previous work clearly showed that multiple classifier systems are effective only if the classifiers forming them are accurate and(More)
Although fingerprint verification systems reached a high degree of accuracy, it has been recently shown that they can be circumvented by " fake fingers " , namely, fingerprint images coming from stamps reproducing an user fingerprint, which is processed as an " alive " one. Several methods have been proposed for facing with this problem, but the issue is(More)