Treillis de concepts et classification supervisée

摘要: Supervised classification is a two-step process. The first step (learning step) consists in building model (or classifier) describing predetermined set of data classes. In the second (classification step), used to predict class label previously unseen objects. this paper we present different concept lattices-based supervised methods. We describe learning and principle each method, their algorithm complexity. also experimental comparison results obtained with other methods, as reported literature. discuss advantages limitations lattices for classification.