New classification technique using neural networks and genetic algorithms

被引：0
|
作者：
Bailoul, Charaf Eddine [1 ]
Alaa, Nour Eddine [1 ]
机构：
[1] Univ Cadi Ayyad, Fac Sci & Technol, Lab LAMAI, 112 Blvd Abdelkr Al Khattabi, Marrakech, Morocco
来源：
ANNALS OF THE UNIVERSITY OF CRAIOVA-MATHEMATICS AND COMPUTER SCIENCE SERIES | 2019年 / 46卷 / 02期
关键词：
Neural networks; Classification; Error function; Backpropagation; Genetic algorithms; Confusion matrix;
D O I：
暂无
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
Classification is a data mining technique used to predict group membership for data instances, and its one of the most active research and application areas of neural networks. There are several classification techniques that can be used for classification purpose. In this paper, we develop a new classification technique using neural networks and genetic algorithms. A comparison with the classical backpropagation algorithm is also given. Furthermore, various numerical experiments are presented to confirm the accuracy and efficiency of our proposed technique.
引用
收藏
页码：433 / 444
页数：12
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