GENE SELECTION FOR BREAST CANCER CLASSIFICATION BASED ON DATA FUSION AND GENETIC ALGORITHM

被引：0
作者：
Yildiz, Oktay [1 ]
Tez, Mesut [2 ]
Bilge, H. Sakir [1 ]
Akcayol, M. Ali [1 ]
Guler, Inan [3 ]
机构：
[1] Gazi Univ, Muhendisl Fak, Bilgisayar Muhendisligi Bol, Ankara, Turkey
[2] Ankara Numune Hastanesi, Ankara, Turkey
[3] Gazi Univ, Tekn Egitim Fak, Elekt Bilgisayar Egitimi Bol, Ankara, Turkey
来源：
JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY | 2012年 / 27卷 / 03期
关键词：
Data Mining; Feature Selection; Data Fusion; Genetic Algorithm; Breast Cancer; Support Vector Machine; EXPRESSION DATA; PARAMETERS; MACHINE;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Early diagnosis of breast cancer has been playing very important role on treatment of the disease. In this work, a new feature selection method for breast cancer classification based on data fusion and genetic algorithm is presented. The study consists of two steps: In the first step, the dimensionality of the gene expression dataset was reduced with filter method and the second step, significant genes have been identified with genetic algorithm. SVM was used for fitness function in genetic programming. In this study the classification accuracy rate was obtained 94.65 % when using selected 10 genes.
引用
收藏
页码：659 / 668
页数：10
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