Diagnosis of Breast Cancer Tumor Based on ICA and LS-SVM

An efficient method for the diagnosis of breast cancer tumor is proposed based on independent component analysis (ICA) and least square support vector machine (LS-SVM). In order to save the expense of detection, firstly, variables are selected based on the theory of statistics. Then the ICA is introduced in a concise way and followed by extracting the ICA component from these selected variables. Finally the processed data are classified by the LS-SVM. Experimental and analytical results show that in the diagnosis of breast cancer tumor the proposed method is superior to the classical BP algorithm