Comparative Analysis of Artificial Neural Network and Support Vector Machine Classification for Breast Cancer Detection
Prachi Damodhar Shahare, Ram Nivas Giri · 2015
Prachi Damodhar Shahare1, Ram Nivas Giri2 1 M.Tech Scholar, Department of CSE, Raipur Institute of Technology, Raipur, India 2 Assistant Professor, Department of CSE, Raipur Institute of Technology, Raipur, India ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract Breast cancer is one of most hazardous types of cancer among women in the world. It is a complex disease characterized by many morphological, clinical and molecular features. It is an uncontrolled growth of breast cells. Soft Computing has become popular in developing systems that encloses human expertise. Imaging technologies and clinical cytology have improved breast cancer diagnosis, better survival rates and treatment by early detection of primary or metastatic masses, differentiating benign from malignant tumors and promoting intraoperative surgical guidance and post operative specimen evaluation. Medical results produce undesirable faults and extreme clinical costs which influence the value of services offered to patients. Hence, exact detection is extremely important for proper treatment and cure of disease. Precise outcome can be achieved using Artificial Neural Network. Different kernel functions of Support Vector Machine are used for classification of breast cancer dataset. The comparative analysis of both ANN and SVM is done for performance evaluation in terms of accuracy. The dataset used in this research is taken from UCI database composed of 683 cytological instances, out of which 458 are benign and 241 are malignant. The results show a better performance for SVM classifier than ANN.