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
收藏
页码：115 / 135
页数：21
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