Bagging Evolutionary ROC-based Hypotheses Application to Terminology Extraction.
Azé Jérôme, Roche Mathieu and Sebag Michèle
In: ROCML 2005 (ROC Analysis in ML), 11 August 2005, Bonn, Germany.
The claim of the paper is that Evolutionary Learning is a source of diverse hypotheses “for free”, and this specificity canbe used to combine in an ensemble the hypotheses learned in independent runs. The aim of our algorithm named Broger (Bagging-ROC GEnetic LEarneR) consists of optimizing the Area Under theROC Curve usingEvolutionary Learning. This paper first presents the theoretical framework of Broger and then its application to a Term Extraction task in Text Mining.