In this work we show that entropy (H) and mutual information (MI) can be used as methods for extracting spatially localized features for classification purposes. In order to incre...
Liang Wu, Predrag Neskovic, Etienne Reyes, Elena F...
We consider the problem of classifying documents not by topic, but by overall sentiment, e.g., determining whether a review is positive or negative. Using movie reviews as data, 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...
Abstract Dino Ienco and Rosa Meo Dipartimento di Informatica, Universit`a di Torino, Italy In this paper we propose and test the use of hierarchical clustering for feature selectio...
Incorporating semantic features from the WordNet lexical database is among one of the many approaches that have been tried to improve the predictive performance of text classifica...