不确定数据的一个支持向量机分类方法

A Support Vector Machine Classification Method For Uncertain Data

给出了输入数据含有不确定信息的一个支持向量机分类方法.通过未确知数理论,得到支持向量机分类的一个概率约束模型,然后通过一定方法将概率约束转化为一般约束,由此将给出的概率约束优化模型转化为一个确定性支持向量机分类模型,从而有效解决了含有不确定数据的分类计算问题.

In this paper,a support vector machine classification approach with input data uncertainty was proposed. By the uncertain data theory,a probabilistic constraint model was given to support vector machine classification. By transforming the probabilistic constraint into a deterministic constraint,a deterministic support vector machine classification model was suggested. The classification problem with uncertain data was effectively solved.