Approximate polytope ensemble for one-class classification

P. Casale, O. Pujol, P. Radeva

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

29 Citaten (Scopus)

Samenvatting

In this work, a new one-class classification ensemble strategy called Ap-proximate Polytope Ensemble is presented. The main contribution of the paper is threefold. First, the geometrical concept of convex hull is used to define the boundary of the target class defining the problem. Expan-sions and contractions of this geometrical structure are introduced in order to avoid over-fitting. Second, the decision whether a point belongs to the convex hull model in high dimensional spaces is approximated by means of random projections and an ensemble decision process. Finally, a tiling strategy is proposed in order to model non-convex structures. Experimental results show that the proposed strategy is significantly better than state of the art one-class classification methods on over 200 datasets.
Originele taal-2Engels
Pagina's (van-tot)854-864
Aantal pagina's11
TijdschriftPattern Recognition
Volume47
Nummer van het tijdschrift2
DOI's
StatusGepubliceerd - 2014

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