Support Vector Machine Classifier with WHM Offset for Unbalanced Data
2008 ◽
Vol 12
(1)
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pp. 94-101
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Keyword(s):
We propose an improved support vector machine (SVM) classifier by introducing a new offset, for solving the real-world unbalanced classification problem. The new offset is calculated based on the unbalanced support vectors resulting from the unbalanced training data. We developed a weighted harmonic mean (WHM) algorithm to further reduce the effects of noise on offset calculation. We apply the proposed approach to classify real-world data. Results of simulation demonstrate the effectiveness of our proposed approach.
2014 ◽
Vol 229
(3)
◽
pp. 580-588
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2011 ◽
Vol 10
(04)
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pp. 481-494
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Keyword(s):
Keyword(s):
2010 ◽
Vol 19
(05)
◽
pp. 647-677
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Keyword(s):
Keyword(s):
2014 ◽
Vol 609-610
◽
pp. 1448-1452
2020 ◽
Vol 8
(5)
◽
pp. 1557-1560