Fuzzy Support Vector Machine for breast cancer gene classification

In this paper, an effective feature selection method to extract high-dimensional feature of breast cancer was proposed, and designed a geometric mean KNN (K-Nearest Neighbor) membership function and L-KMOD kernel function FSVM (Fuzzy Support Vector Machine) to recognize breast cancer gene, when selecting 60 feature genes, the classification accuracy can achieve 98.9%.