Comparing the Behavior of Oversampling and Undersampling Approach of Class Imbalance Learning by Combining Class Imbalance Problem with Noise-Reference-Cited by-同舟云学术

Comparing the Behavior of Oversampling and Undersampling Approach of Class Imbalance Learning by Combining Class Imbalance Problem with Noise

Published:2017-10-01 Issue: Volume: Page:23-30
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
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Author:

Kaur Prabhjot,Gosain Anjana

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-10-6602-3_3

Reference24 articles.

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2. Garcia, V., et. al.: The class imbalance problem in pattern classification and learning. Pattern analysis and learning group, Conreso Espanol de Informatica; pp. 283–291

3. Napierala, K., et. al.: Learning from Imbalance data in presence of Noisy and Borderline Examples. RSCTC, LNAI 6086, pp. 158–167, Springer-Verlag, Berlin Heidelberg (2010)

4. Satyashree, K.P.N.V., Murthy, J.V.R.: An exhaustiv literature review on class imbalance problem. Int. J. Emerging Trends Technol. Comput. Sci. 2(3), 109–118 (2013)

5. Fernandez, A., et al.: A study of the behaviour of linguistic fuzzy rule base classification systems in the framework of imbalanced data-sets. Fuzzy Sets Syst. 159(18), 2378–2398 (2008)

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