如多分类器系统 Multiple Classifiers Systems
The research results show that multiple classifiers system has been more effected by the research of the relationship between member of classifiers and the improvement of the whole procedure.
结果表明,各种方法有着各自的适应性,多分类器系统的研究应更关注分类器之间的关系研究及系统各环节的整体改进。
参考来源 - 基于融合决策的多分类器系统研究·2,447,543篇论文数据，部分数据来源于NoteExpress
为改善多分类器系统的分类性能，提出了基于广义粗集的集成特征选择方法。
For improving the performance of multiple classifier system, a novel method of ensemble feature selection is proposed based on generalized rough set.
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。
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.
针对标准数据集在评估多分类器系统的组合方法时存在的不足，设计了一种新的分类器模拟算法。
Aiming at the deficiency of evaluating classifier combination methods with standard data sets, a new classifier simulation algorithm was proposed.
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