HYBRID NEURO-FUZZY CLASSIFIER BASED ON NEFCLASS MODEL

被引：0

作者：

Gliwa, Bogdan ^{[1
]}

Byrski, Aleksander ^{[1
]}

机构：

[1] AGH Univ Sci & Technol, Fac Elect Engn Automat IT & Elect, Dept Comp Sci, Al A Mickiewicza 30, PL-30059 Krakow, Poland

来源：

COMPUTER SCIENCE-AGH | 2011年 / 12卷

关键词：

Neuro-fuzzy classifier; NEFCLASS; neural networks; fuzzy systems;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The paper presents hybrid neuro-fuzzy classifier, based on NEFCLASS model, which was modified. The presented classifier was compared to popular classifiers - neural networks and k-nearest neighbours. Efficiency of modifications in classifier was compared with methods used in original model NEFCLASS (learning methods). Accuracy of classifier was tested using 3 datasets from UCI Machine Learning Repository: iris, wine and breast cancer wisconsin. Moreover, influence of ensemble classification methods on classification accuracy was presented.

引用

页码：115 / 135

页数：21

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