Directly Identify Unexpected Instances in the Test Set by Entropy Maximization

  • Chaofeng Sha
  • Zhen Xu
  • Xiaoling Wang
  • Aoying Zhou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5446)


In real applications, a few unexpected examples unavoidably exist in the process of classification, not belonging to any known class. How to classify these unexpected ones is attracting more and more attention. However, traditional classification techniques can’t classify correctly unexpected instances, because the trained classifier has no knowledge about these. In this paper, we propose a novel entropy-based method to the problem. Finally, the experiments show that the proposed method outperforms previous work in the literature.


Text Data Severe Acute Respiratory Syndrome Nominal Data Positive Class Negative Instance 
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  1. 1.
    Liu, B., Dai, Y., Li, X., Lee, W., Yu, S.: Building Text Classifiers Using Positive and Unlabeled Examples. In: IJCAI 2003 (2003)Google Scholar
  2. 2.
    Györfi, L., Györfi, Z., Vajda, I.: Bayesian decision with rejection. Problems of Control and Information Theory 8, 445–452 (1978)MathSciNetzbMATHGoogle Scholar
  3. 3.
    Devroye, L., Györfi, L., Lugosi, G.: A Probabilistic Theory of Pattern Recognition. Springer, Heidelberg (1996)CrossRefzbMATHGoogle Scholar
  4. 4.
    Cover, T., Thomas, J.: Elements of information theory. Wiley Interscience, Hoboken (1991)CrossRefzbMATHGoogle Scholar
  5. 5.
    Li, X., Liu, B., Lee, W., Yu, S.: Text Classificaton by Labeling Words. In: AAAI 2004 (2004)Google Scholar
  6. 6.
    Li, X., Liu, B., Ng, S.: Learning to identify unexpected instances in the test set. In: IJCAI 2007 (2007)Google Scholar
  7. 7.
    Guo, Y., Greiner, R.: Optimistic active learning using mutual information. In: IJCAI 2007 (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Chaofeng Sha
    • 1
  • Zhen Xu
    • 1
  • Xiaoling Wang
    • 2
  • Aoying Zhou
    • 2
  1. 1.Department of Computer Science and EngineeringFudan UniversityShanghaiChina
  2. 2.Shanghai Key Laboratory of Trustworthy Computing Institute of Massive ComputingEast China Normal UniversityShanghaiChina

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