A Comparative Study of Improved F-Score with Support Vector Machine and RBF Network for Breast Cancer Classification
P. Jaganathan, N. Rajkumar, R. Kuppuchamy · International Journal of Machine Learning and Computing · 2012
Feature selection is an important issue in classification of cancer diagnosis.In this paper, a new feature selection method, named improved F-Score is applied for breast cancer diagnosis.First, the improved F-Score values of all the features are calculated using improved F-Score formula.Then the mean value is computed for the calculated improved F-Score values.The improved F-Score values which are greater than the mean improved F-Score are selected.Wisconsin breast cancer dataset (WBCD) is used in this study.As classification algorithms, Support Vector Machine and RBF Network are sued.The results obtained from improved F-Score with Support Vector Machines have produced efficient results compared to improved F-Score with RBF Network.Therefore we show that improved F-Score combined with promising than improved F-Score with RBF Network.