In this paper we present a study on the Random Forest (RF) family of ensemble methods. From our point of view, a "classical" RF induction process presents two main drawba...
Decision trees are among the most effective and interpretable classification algorithms while ensembles techniques have been proven to alleviate problems regarding over-fitting and...
Abstract. Ensemble methods are able to improve the predictive performance of many base classifiers. Up till now, they have been applied to classifiers that predict a single target ...
Dragi Kocev, Celine Vens, Jan Struyf, Saso Dzerosk...
As unlexicalized parsing lacks word token information, it is important to investigate novel parsing features to improve the accuracy. This paper studies a set of tree topological ...
Samuel W. K. Chan, Lawrence Y. L. Cheung, Mickey W...
Previous work on dependency parsing used various kinds of combination models but a systematic analysis and comparison of these approaches is lacking. In this paper we implemented ...