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A NOVEL FUZZY CLASSIFIER ENSEMBLE SYSTEM

机译:新型模糊分类器系统

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摘要

In this paper,a novel fuzzy classifier ensemble system is proplsed.This system can reduce subjective factor in building a fuzzy classifier,and improve the classification recognition rate and stability.Three proplsed approaches are introduced,namely,the approach of measuring generalization difference(GD)of classifier sssets to select individual classifiers,the approach of determining individual classifier's reliability by the proposed membership matrix,the approach of classifier ensemble.The proplsed systeM is evaluated with standard data sets.The comparison of experiments and the existed classifier ensemble systems.The experiment results show that the recognition rate of our proplsed system is higher than ones of other classifier ensemble systems.
机译:本文提出了一种新颖的模糊分类器集成系统。该系统可以减少构建模糊分类器的主观因素,提高分类识别率和稳定性。介绍了三种分类方法,即度量广义差异的方法分类器集合)以选择单个分类器,通过拟议的隶属度矩阵确定单个分类器的可靠性的方法,分类器集合的方法。用标准数据集评估被推进的系统。实验与现有分类器集合系统的比较。实验结果表明,该推进系统的识别率高于其他分类器集成系统。

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