Alleviating class imbalance problem in data mining;Veri madenciliǧindeki sinif dengesizliǦinin giderilmesi

2013 21st Signal Processing and Communications Applications Conference, SIU 2013

Volumn , Issue , 2013, Pages

  Sarmanova, Akkenzhe ^a   Albayrak, Songül ^a  

^a YILDIZ TECHNICAL UNIVERSITY   (Turkey)

Author keywords

Binary classification; Boosting; Class imbalance; Resampling

Indexed keywords

BINARY CLASSIFICATION; BOOSTING; CLASS IMBALANCE; CLASS IMBALANCE PROBLEMS; RESAMPLING; STANDARD MACHINES; TRAINING DATA SETS;

SIGNAL PROCESSING;

LEARNING ALGORITHMS;

EID: 84880898646     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SIU.2013.6531574     Document Type: Conference Paper

References (6)

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3. Hongyu Guo, Herna L Viktor, "Learning from Imbalanced Data Sets with Boosting and Data Generation: The DataBoost-IM Approach", ACM SIGKDD Explorations Newsletter, 2004.
4. Seiffert C., Khoshgoftaar T. M., Van Hulse J., & Napolitano A., RUSBoost: A Hybrid Approach to Alleviating Class Imbalance. Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, 40(1), 185-197, 2010.
5. J. Van Hulse, T. M. Khoshgoftaar, and A. Napolitano, "Experimental perspectives on learning from imbalanced data, " in Proc. 24th Int. Conf. Mach. Learn., Corvallis, OR, Jun. 2007, pp. 935-942.
6. Xu-Ying Liu, Jianxin Wu, and Zhi-Hua Zhou. Exploratory undersampling for class imbalance learning. IEEE Transactions on Systems, Man and Cybernetics, 39(2):539-550, 2009.