%0 Journal Article
%T When does Active Learning Work?
%A Lewis Evans
%A Niall M. Adams
%A Christoforos Anagnostopoulos
%J Computer Science
%D 2014
%I arXiv
%X Active Learning (AL) methods seek to improve classifier performance when labels are expensive or scarce. We consider two central questions: Where does AL work? How much does it help? To address these questions, a comprehensive experimental simulation study of Active Learning is presented. We consider a variety of tasks, classifiers and other AL factors, to present a broad exploration of AL performance in various settings. A precise way to quantify performance is needed in order to know when AL works. Thus we also present a detailed methodology for tackling the complexities of assessing AL performance in the context of this experimental study.
%U http://arxiv.org/abs/1408.1319v1