A new hybrid classifier system:: Information gain-based artificial immune recognition system

被引：2
|
作者：
Kodaz, H. [1 ]
Kara, S.
Latioglu, F.
Gunes, S.
机构：
[1] Selcuk Univ, Dept Comp Engn, Konya, Turkey
[2] Erciyes Univ, Dept Elect Engn, Kayseri, Turkey
[3] Selcuk Univ, Dept Elect & Elect Engn, Konya, Turkey
来源：
EXPERIMENTAL TECHNIQUES | 2007年 / 31卷 / 06期
关键词：
DIAGNOSIS; DISTENSIBILITY; SELECTION;
D O I：
10.1111/j.1747-1567.2007.00179.x
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
A new hybrid system called information gain-based artificial immune recognition system (IG-AIRS) has been proposed involving two stages. First, obtainment of information gain values of data attribute and second, application of gain values to the artificial immune recognition system with information-based Euclidean distance. At the same time, a diagnostic system leading to a more effective usage of the Doppler technique is presented using the maximum envelope of the carotid artery Doppler sonograms derived from the fast Fourier transformation-based Welch method and the IG-AIRS to distinguish between atherosclerosis and other health issues. The accuracy of classification for the atherosclerosis disease data set reached 99.09% for optimum parameter values using the 10-fold cross validation method.
引用
收藏
页码：36 / 43
页数：8
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