A survey of recent trends in one class classification

Khan, Shehroz S., & Madden, Michael G. (2009). A survey of recent trends in one class classification. Paper presented at the 20th Artificial Intelligence and Cognitive Science Conference (AICS), Dublin, Ireland, 19-21 August.

Abstract

The One Class Classification (OCC) problem is di fferent from the conventional binary/multi-class classi fication problem in the sense that in OCC, the negative class is either not present or not properly sampled. The problem of classifying positive (or target) cases in the absence of appropriately-characterized negative cases (or outliers) has gained increasing attention in recent years. Researchers have addressed the task of OCC by using diff erent methodologies in a variety of application domains. In this paper we formulate a taxonomy with three main categories based on the way OCC has been envisaged, implemented and applied by various researchers in different application domains. We also present a survey of current state-of-the-art OCC algorithms, their importance, applications and limitations.

Publisher

Springer Verlag - LNAI

Rights

Attribution-NonCommercial-NoDerivs 3.0 Ireland

cbn

Collections

Computer Science (Conference Papers)
Computer Science (Scholarly Articles)