Existing cost-sensitive learning methods work with unequal misclassification cost that is given by domain knowledge and appears as precise values. In many real-world applications,...
Classifiers are traditionally learned using sets of positive and negative training examples. However, often a classifier is required, but for training only an incomplete set of pos...
When we have several related tasks, solving them simultaneously is shown to be more effective than solving them individually. This approach is called multi-task learning (MTL) and...
We investigate the performance of two machine learning algorithms in the context of antispam filtering. The increasing volume of unsolicited bulk e-mail (spam) has generated a nee...
Ion Androutsopoulos, Georgios Paliouras, Vangelis ...
Fold recognition is a key problem in computational biology that involves classifying protein sharing structural similarities into classes commonly known as "folds". Rece...