Abstract. Stability is an important property of machine learning algorithms. Stability in clustering may be related to clustering quality or ensemble diversity, and therefore used ...
Maurizio Filippone, Francesco Masulli, Stefano Rov...
This paper describes a theoretical approach on data mining, information classifying and a global overview of our OntoExtractor application, concerning the analysis of incoming data...
Zhan Cui, Ernesto Damiani, Marcello Leida, Marco V...
Ensembles are often capable of greater prediction accuracy than any of their individual members. As a consequence of the diversity between individual base-learners, an ensemble wil...
Vladimir Nikulin, Geoffrey J. McLachlan, Shu-Kay N...
We introduce a multi-stage ensemble framework, ErrorDriven Generalist+Expert or Edge, for improved classification on large-scale text categorization problems. Edge first trains a ...
The "minimum margin" of an ensemble classifier on a given training set is, roughly speaking, the smallest vote it gives to any correct training label. Recent work has sh...