...的任意二元组(xi,yi)，满足: 当 时 当 时 可以统一起表示为: 其中，满足上式的超平面就是分类超平面（Seperating Hyperplane）。在样本线性可分时，存在无数个这样的超平面。
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...属性空间；分类超平面 [gap=1158]Key words: SVM; classification of DNA; feature attribute space; classification hyperplane ...
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最优分类超平面原理使SVM在解决线性可分问题时有很好的表现。
The principle of finding optimized decision boundary give SVM excellent performance on linear separatable problems.
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。
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.
该类学习机利用线性聚类，提取距分类超平面较近的样本构造改进的学习机。
The training data close to the hyperplane are extracted to form the improved learning machines by using linear clustering.
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