Feature selection is often applied to highdimensional data prior to classification learning. Using the same training dataset in both selection and learning can result in socalled ...
– Packet classification on multiple header fields is one of the basic techniques used in network devices such as routers and firewalls, and usually the most computation intensive...
Classification problems are traditionally focused on uniclass samples, that is, each sample of the training and test sets has one unique label, which is the target of the classific...
Manual classification of free-text documents within a predefined hierarchy is highly time consuming. This is especially true for clinical guidelines, which are often indexed by mu...
Robert Moskovitch, Shiva Cohen-Kashi, Uzi Dror, If...
Abstract. Many supervised machine learning tasks can be cast as multi-class classification problems. Support vector machines (SVMs) excel at binary classification problems, but the...