Learning over subconcepts: Strategies for 1-class classification
Author:
Affiliation:
1. School of Information Technology and Engineering; University of Ottawa; Canada
2. School of Computer Science; Carleton University; Canada
Funder
Canadian government through an NSERC/ISTP CRD
Publisher
Wiley
Subject
Artificial Intelligence,Computational Mathematics
Link
http://onlinelibrary.wiley.com/wol1/doi/10.1111/coin.12128/fullpdf
Reference24 articles.
1. Learning from imbalanced data;He;IEEE Trans Knowl Data Eng,2009
2. Bellinger C Sharma S Japkowicz N One-class versus binary classification: which and when? 2012 102 106
3. Stocki TJ Japkowicz N Ungar IK Hoffman J Yi J Summary of the data mining contest for the IEEE International Conference on Data Mining Pisa, Italy IEEE 2008 1 6 http://www.cs.uu.nl/groups/ADA/icdm08cup/booklet.pdf
4. Machine learning for radioxenon event classification for the Comprehensive Nuclear-Test-Ban Treaty;Stocki;J Environ Radioact,2010
5. Class imbalances: are we focusing on the right issue?;Japkowicz;Workshop on Learning from Imbalanced Data Sets II.,2003
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