When more than a single classifier has been trained for the same recognition problem the question arises how this set of classifiers may be combined into a final decision rule. Se...
Abstract. A large experiment on combining classifiers is reported and discussed. It includes, both, the combination of different classifiers on the same feature set and the combina...
Selecting a set of good and diverse base classifiers is essential for building multiple classifier systems. However, almost all commonly used procedures for selecting such base cla...
We propose a novel unsupervised approach for distinguishing literal and non-literal use of idiomatic expressions. Our model combines an unsupervised and a supervised classifier. T...
The use of multiple features by a classifier often leads to a reduced probability of error, but the design of an optimal Bayesian classifier for multiple features is dependent on t...