Since multiple classifier systems(MCS) can improve the performance of classification, the technique has been widely used in various fields of pattern recognition.
多分类器组合方法可以在一定程度上弥补单个分类器的不足，提高分类性能，因此，它在模式识别领域得到广泛的应用。
Since multiple classifier systems can to some extent improve the performance of classification, the technique has been widely used in various fields of pattern recognition.
多分类器系统能够在一定程度上弥补单个分类器的缺陷，因此它在模式识别中得到了广泛的应用。
The experiments on UCI Machine Learning Repository prove that, compared to existing measures, EPD shows stronger ability in predicting the performance of multiple classifier systems.
对UCI机器学习数据库的实验证明，相对于其它方法，EPD方法对多分类器系统性能的预测能力更强。
Aiming at improving the classification performance, a combination model of multiple classifier systems is presented, which takes the Sum rule and majority voting as its special cases.
为改进多分类器系统的性能，提出一个多分类器融合模型，该模型将和规则与多数投票作为特例纳入其体系中。
Aiming at improving the classification performance, a combination model of multiple classifier systems is presented, which takes the Sum rule and majority voting as its special cases.
为改进多分类器系统的性能，提出一个多分类器融合模型，该模型将和规则与多数投票作为特例纳入其体系中。
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