Title :
Research on medical diagnostic decision-making based on attribute reduction and support vector machines
Author :
Hu, Zhonghui ; Li, Yuangui ; Cai, Yunze ; Xu, Xiaoming
Author_Institution :
Dept. of Autom., Shanghai Jiaotong Univ., China
Abstract :
The method of attribute reduction is applied to medical diagnostic decision by combining basic theory of support vector machines for nonlinear classification. Decision-making performance of the proposed method is compared with that of the conventional methods. The results indicate our method can decrease the computation complexity and memory requirement a lot, particularly for the large and high dimension data set. Furthermore, the decision-making power remains still good.
Keywords :
classification; computational complexity; decision making; medical diagnostic computing; support vector machines; attribute reduction; computation complexity; medical diagnostic decision-making; memory requirement; nonlinear classification; support vector machines; Automation; Computational complexity; Decision making; Kernel; Machine intelligence; Machine learning; Medical diagnosis; Statistical learning; Support vector machine classification; Support vector machines;
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
DOI :
10.1109/WCICA.2004.1343077
