DIAGNOSIS OF BREAST CANCER TUMOR BASED ON ICA AND LS-SVM

摘要：

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 B-P algorithm.

关键词： Independent Component Analysis Least Square Support Vector Machine Breast cancer tumor

作者: CHAO-YONG WANG CHUN-GUO WU YAN-CHUN LIANG XIN-CHEN GUO

作者单位: College of Computer Science and Technology, Jilin University, Key Laboratory of Symbol Computation a College of Computer Science and Technology, Jilin University, Key Laboratory of Symbol Computation a College of Computer Science and Technology, Jilin University, Key Laboratory of Symbol Computation a

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 2565-2570

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）