A survey of recent trends in one class classification
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Date
2009-08Author
Khan, Shehroz S.
Madden, Michael G.
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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.