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中文摘要：
支持向量机和粗糙集理论是两种分类技术。前者寻求最大化两类间隔的最优分类超平面，后者用逻辑规则解释分类。基于两者的关系，提出了一种复合算法，且将其推广到回归。新算法在一定程度降低了计算复杂度，且适用于软间隔分类。数值实验表明新算法是有效可行的。
英文摘要：
Support vector machine （SVM） and rough set （RS） theory are two classification techniques. The former attempts to find an optimal hyperplane that maximize margin between two classes, and the later are designed to provide an explanation of the classification using logical rules. A compact algorithm is proposed based on the relationship between their principles. This new algorithm can reduce the complexity of computation to a certain degree and is especially useful for soft margin classifier; also it is generalized to regression. Numerical results illustrate that the algorithm is feasible and effective.
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