Ensemble learning algorithms such as boosting can achieve better performance by averaging over the predictions of some base hypotheses. Nevertheless, most existing algorithms are ...
In this paper, a hybrid discriminative/generative model for brain anatomical structure segmentation is proposed. The learning aspect of the approach is emphasized. In the discrimin...
In this paper we study supervised and semi-supervised classification of e-mails. We consider two tasks: filing e-mails into folders and spam e-mail filtering. Firstly, in a sup...
Irena Koprinska, Josiah Poon, James Clark, Jason C...
In this paper, we evaluate and investigate two main types of relevance feedback algorithms; the Euclidean and the correlation?based approaches. In the first case, we examine heuri...
We describe experiments with a Naive Bayes text classifier in the context of anti-spam E-mail filtering, using two different statistical event models: a multi-variate Bernoulli ...