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...
: Error rates in the assessment of routine claims for welfare benefits have been found to very high in Netherlands, USA and UK. This is a significant problem both in terms of quali...
Maya Wardeh, Trevor J. M. Bench-Capon, Frans Coene...
In this paper, we investigate the use of a machine-learning based approach to the specific problem of scientific term detection in patient information. Lacking lexical databases w...
In this paper we propose and test the use of hierarchical clustering for feature selection. The clustering method is Ward's with a distance measure based on GoodmanKruskal ta...
We introduce the notion of restricted Bayes optimal classifiers. These classifiers attempt to combine the flexibility of the generative approach to classification with the high ac...