计算机工程与应用 ›› 2010, Vol. 46 ›› Issue (10): 36-37.DOI: 10.3778/j.issn.1002-8331.2010.10.012
• 研究、探讨 • 上一篇 下一篇
何渊淘，邓 伟
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HE Yuan-tao，DENG Wei
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摘要： 将一种改进的邻域算法应用于不均衡样本集中，由于改进的邻域算法未考虑不均衡样本集的问题从而导致后续的支持向量机训练耗费和泛化性能受影响，把后验概率的思想加入改进的邻域算法中，并由实验数据说明了该方法对不均衡样本集的有效性。
关键词: 支持向量机（SVM）, 邻域算法, 后验概率, VC维
Abstract: An improved neighborhood algorithm is applied in unbalance data set.Because of not considering unbalance date set，the generalization of improved neighborhood algorithm is degrade.In order to solve this problem，the idea of posterior probability is used in the new neighborhood algorithm and the result of pattern classification shows the effectiveness of the method.
Key words: Support Vector Machine（SVM）, neighborhood algorithm, posterior probability, VC dimension
中图分类号:
TP183
何渊淘，邓 伟. 改进的不均衡样本集支持向量机预处理方法[J]. 计算机工程与应用, 2010, 46(10): 36-37.
HE Yuan-tao，DENG Wei. Improvement on preprocessing algorithm of support vector machines for unbalance data set[J]. Computer Engineering and Applications, 2010, 46(10): 36-37.
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链接本文: http://cea.ceaj.org/CN/10.3778/j.issn.1002-8331.2010.10.012
http://cea.ceaj.org/CN/Y2010/V46/I10/36
