Abstract:Data driven prognostic models are becoming more prevalent in many areas, ranging from heavy trucks to gas turbines. One aspect of certain prognostic models is the need for labeled failures, which then can be used as positive examples, when modelling the prognostic problem. Unfortunately, standard algorithms for creating prognostic models can suffer when labeled data is unbalanced, w.r.t. class distribution, leading to prognostic models with poor performance. In this paper we present a methodology for creating … Show more
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.