Title :
Mining rules based on elastic trust granular
Author :
Nie, Bin ; Du, Jianqiang ; Liu, Hongning ; Yu, Riyue ; Wang, Zhuo
Author_Institution :
Sch. of Comput., Jiang Xi Univ. of Traditional Chinese Med., Nanchang, China
Abstract :
Uncertainty and imprecision problem is a common phenomenon in the medical diagnosis, this paper present a novel method to deal with it. The first, some new concepts such as elastic trust, elastic trust granular (ETG), inclusion and similarity relation of elastic trust (ISRET), and so on are introduced. The second, on that basis, the paper puts forward a novel distance of elastic trust granular, such as inclusion and diversity/similarity relation distance of elastic trust granular (IDSRDETG), The third, mining rules based on these concepts, is discussed. It was proved to be feasible and effective after tested with a database.
Keywords :
data mining; medical computing; patient diagnosis; rough set theory; uncertainty handling; diversity-similarity relation distance of elastic trust granular; elastic trust granular; inclusion and similarity relation of elastic trust; medical diagnosis; rules mining; Cardiology; Kidney; Rough set; diagnostic rules; elastic trust granular; the distance of elastic trust granular;
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
DOI :
10.1109/ICCASM.2010.5620066