BERT: Melhorando Classificação de Texto com Árvores Extremamente Aleatórias, Bagging e Boosting

Abstract

One of the most effective methods for text classification is the recently proposed BROOF classifier, a boosted version of Random Forest (RF). In this work, we propose to improve the BROOF strategy by exploiting Extremely Randomized Trees (Extra-Trees) as a “weak learner” in the boosting framework. In this context, we also introduce the Bagging procedure… (More)

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