TUTCRIS - Tampereen teknillinen yliopisto

TUTCRIS

One-Class Classification based on Extreme Learning and Geometric Class Information

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
Sivut1-16
Sivumäärä16
JulkaisuNeural Processing Letters
DOI - pysyväislinkit
TilaJulkaistu - 2016
OKM-julkaisutyyppiA1 Alkuperäisartikkeli

Tiivistelmä

In this paper, we propose an extreme learning machine (ELM)-based one-class classification method that exploits geometric class information. We formulate the proposed method to exploit data representations in the feature space determined by the network hidden layer outputs, as well as in ELM spaces of arbitrary dimensions. We show that the exploitation of geometric class information enhances performance. We evaluate the proposed approach in publicly available datasets and compare its performance with the recently proposed one-class extreme learning machine algorithm, as well as with standard and recently proposed one-class classifiers. Experimental results show that the proposed method consistently outperforms the remaining approaches.