Any class in the underlying ontology can be used as a classifier; the same classifier can be used to classify multiple entities and an entity can be associated with multiple classifiers.
基础本体中的任何类都可以用作分类器；可以使用同一分类器来对多个实体进行分类，并且一个实体可以与多个分类器关联。
The combination of multiple classifiers is one of the effective ways to improve the recognition performance.
多分类器组合是提高识别效果的一条有效途径。
Therefore, it is theoretically and practically significant to study the method of combining multiple classifiers and explore its application in automatic classification of remote sensing images.
因此，进行多分类器组合研究，探讨其在遥感影像自动分类中的应用，具有重要的理论与实践意义。
The multiple classifiers combination fuses the decision level data.
多分类器组合是对决策层的数据进行融合。
A combination of multiple classifiers is a powerful solution to difficult pattern recognition problem.
多分类器联合是解决复杂模式识别问题的有效办法。
A combination of multiple classifiers is a powerful solution to the difficult pattern recognition problem.
多分类器联合是解决复杂模式识别问题的有效办法。
The methods of multiple classifiers combination are proposed to classify protein-protein interaction sites.
提出将多分类器组合算法应用于蛋白质-蛋白质相互作用位点预测。
There are two strategies for multiple classifiers combination: multiple classifiers fusion and multiple classifiers selection.
多分类器组合策略有两类：多分类器融合和多分类器选择。
In the paper, a new multiple classifiers integrated model of online recognizing natural handwritten Chinese character is presented.
本文提出一种联机识别自然手写体汉字的多分类器集成模型。
A new method of speech emotion recognition via voting combination of multiple classifiers is proposed for improving speech emotion classification rate.
为了提高语音情感的正确识别率，提出一种基于多分类器投票组合的语音情感识别新方法。
The experimental results show that the proposed method can fuse multiple classifiers with low classification error rate based on comprehensible fuzzy systems.
实验结果表明，该方法能够用可理解性好的模糊系统实现低错误率的多分类器融合。
We investigate the theoretical framework of multiple classifiers fusion, and apply the decision template algorithms to classify the protein secondary structural classes.
分析了多分类器融合算法的理论框架，并采用决策模板算法对蛋白质结构类的预测问题进行了研究。
Clustering ensemble is inspired by multiple classifiers ensemble. As a novel research topic, clustering ensemble has been proved to improve the performance of traditional clustering algorithms.
受分类集成技术的启示，聚类集成作为当今的研究热点已被证明能有效地提高传统聚类算法的性能。
Multiple classifiers ensemble is an effective method to solve complex classification problems in pattern recognition field.
多分类器组合是解决复杂模式识别问题的有效办法。
Multiple classifiers combination makes use of the complementarities of different classifiers and different characters to improve recognition correctness.
多分类器组合利用不同分类器、不同特征之间的互补性，提高了组合分类器的识别率。
The experimental results have shown that Combining Multiple Classifiers with different features can result in satisfactory and significant improvement in recognition performance.
实验结果表明：利用多特征组合多分类器的方法可以提高“文本无关”说话人辨认系统的识别率和可靠性。
The experimental results have shown that Combining Multiple Classifiers with different features can result in satisfactory and significant improvement in recognition performance.
实验结果表明：利用多特征组合多分类器的方法可以提高“文本无关”说话人辨认系统的识别率和可靠性。
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