dc.contributor.author | Khan, Shehroz S. | en |
dc.contributor.author | Madden, Michael G. | en |
dc.date.accessioned | 2010-12-03T10:35:53Z | en |
dc.date.available | 2010-12-03T10:35:53Z | en |
dc.date.issued | 2009-08 | en |
dc.identifier.citation | 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. | |
dc.identifier.uri | http://hdl.handle.net/10379/1472 | en |
dc.description.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. | en |
dc.format | application/pdf | en |
dc.language | en | en |
dc.language.iso | en | en |
dc.publisher | Springer Verlag - LNAI | en |
dc.relation | One Class Classification, Survey | en |
dc.relation.ispartofseries | Volume 6206;181-190, | en |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Ireland | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/3.0/ie/ | |
dc.subject | One Class Classification | en |
dc.subject | Outlier Detection | en |
dc.subject | Support Vector Machines | en |
dc.subject | Positive and Unlabeled Data | en |
dc.subject.lcsh | Computer Science, Machine Learning | en |
dc.title | A survey of recent trends in one class classification | en |
dc.type | Conference Paper | en |
dc.description.peer-reviewed | peer-reviewed | en |
nui.item.downloads | 17799 | |