【正文快照】： 1引言综合分类(ensemble classification)指利用多个基分类器的输出以得到更好的分类器,这些基分类是为同一个任务而训练出的,每一个都能单独完成分类任务.
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Refer to instability of single BP neural network classifier, adaptive weighted motion mode ensemble classification algorithm according to output information was proposed based on Adaboost ensemble classification concept.
在此基础上,针对单一BP神经网络分类器的识别率不稳定特点,基于Adaboost集成分类思想提出度量输出信息自适应加权的表面肌电动作模式集成分类算法。
参考来源 - 基于sEMG信号的外骨骼式机器人上肢康复系统研究·2,447,543篇论文数据，部分数据来源于NoteExpress
To resolve combining classifiers decisions among ensemble classification over data streams without labeled examples, a transductive constraint-based learning strategy was proposed.
为了解决在没有已知标签样本的情况下数据流组合分类决策问题，提出一种基于约束学习的数据流组合分类器的融合策略。
Ensemble learning is a research hotspot in machine learning, which can improve generalization performance of classification algorithm.
集成学习是当前机器学习的一个研究热点，它可以提高分类算法的泛化性能。
Compared with the single suppo vector machine method, the support vector machine ensemble method has better classification accuracy.
模拟实验结果表明，该方法具有明显优于单一支持向量机的更高的分类准确率。
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