We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
MEME KANSERİ SINIFLANDIRMASI İÇİN VERİ FÜZYONU VE GENETİK ALGORİTMA TABANLI GEN SEÇİMİ.
- Authors
Yıldız, Oktay; Tez, Mesut; Bilge, H. Şakir; Akcayol, M. Ali; Güler, İnan
- Abstract
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.
- Subjects
TUMOR classification; BREAST cancer statistics; DATA fusion (Statistics); STATISTICAL methods in gene expression; GENETIC algorithms; SUPPORT vector machines; STATISTICAL reliability
- Publication
Journal of the Faculty of Engineering & Architecture of Gazi University / Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi,, 2012, Vol 27, Issue 3, p659
- ISSN
1300-1884
- Publication type
Article