This paper describes a text normalization system for deletion-based abbreviations in informal text. We propose using statistical classifiers to learn the probability of deleting ...
In this paper, we present the LIP6 annotation models for the ImageCLEFannotation 2010 task. We study two methods to train and merge the results of different classifiers in order to...
Ali Fakeri-Tabrizi, Sabrina Tollari, Nicolas Usuni...
This paper reports first results of an empirical study of the precision of classification rules on an independent test set. We generated a large number of rules using a general co...
Many methods for quantitative structure-activity relationships (QSARs) deliver point estimates only, without quantifying the uncertainty inherent in the prediction. One way to qua...
Optimization of the control parameters of genetic algorithms is often a time consuming and tedious task. In this work we take the meta-level genetic algorithm approach to control ...