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Journal of Applied Sciences

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Support Vector Date Description Implemented in Class-Imbalance Learning

MIAO Zhi-min1，HU Gu-yu1，DING Li1，ZHAO Lu-wen2，PAN Zhi-song1   

  1. 1.Institute of Command Automation, PLA University of Science and Technology, Nanjing 210007, China
    2. Institute of Communication Engineering, PLA University of Science and Technology, Nanjing 210007, China
  • Received:2007-07-06 Revised:2007-10-10 Online:2008-01-31 Published:2008-01-31

Cited

7

Abstract: In this paper, an I-SVDD algorithm for two-class imbalance problem is proposed, which based on Support Vector Date Description algorithm. In this algorithm, the C value of SVDD with negative sample is redefined for each sample with data distributing information. We verified the efficiency of algorithm using artificial data and UCI datasets for the data unbalanced classification problem. Compared with SVDD with negative samples, the AUC value of I-SVDD is increased by 12%. Compared with AdaBoost, the recall of positive class is increased by 35%,and the precision increased by 2%.

Key words: imbalanced class distribution, one-class classification, support vector data description(SVDD), AdaBoost