提出一种基于最大熵模型和投票法的汉语动词与动词搭配识别方法。
In this paper, a method for verb-verb collocation recognition is proposed based on maximum entropy model and voting.
本文提出一种以模式聚类为基础的病态样本判定方法，并给出基于模式相似度计算的投票剔除算法。
The author presented a method for morbid sample recognition that base mode clustering, paper proposed a eliminating algorithm of voting that base mode similarity calculating.
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。
A new method of speech emotion recognition via voting combination of multiple classifiers is proposed for improving speech emotion classification rate.
实验结果表明，与基于投票或加权投票的集成方法相比，基于堆叠集成方法对概念漂移的快速适应能力以及预测准确率得到了提高。
Experiments show that comparing majority vote or weight vote ensemble classifiers, stacking ensemble classifiers has stronger ability in adapting to concept drifting and higher accuracy.
实验结果表明，与基于投票或加权投票的集成方法相比，基于堆叠集成方法对概念漂移的快速适应能力以及预测准确率得到了提高。
Experiments show that comparing majority vote or weight vote ensemble classifiers, stacking ensemble classifiers has stronger ability in adapting to concept drifting and higher accuracy.
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