Journal
INTELLIGENT AUTOMATION AND SOFT COMPUTING
Volume 18, Issue 6, Pages 679-686Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/10798587.2012.10643277
Keywords
Support Vector Machine; Imbalance Data; Re-Sampling; K-means clustering
Funding
- National Natural Science Foundation [50878219]
- National Basic Research Program of China [2010CB334710]
- Natural Science Foundation Project of CQ [CSTC2008BA6038, CSTC2009AB6148, CSTC2009AB6149, CSTC2011BA6026]
- Scientific & Technological Research Projects of CQ [10110424]
- Ministry of Education for New Century Excellent Talent Support Program
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Support vector machine has a better classification and prediction performance on balance data classification, but has a poor performance for imbalance data. In this paper, the reason of the poor results which were produced by imbalance data is explained. And a new approach is proposed to solve the imbalance data classification. By this method the imbalance data problem is converted to several independent classifications with balance data and can be trained in parallel. The experiments show that new method has a best effect in some classifying strategy.
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