DocumentCode
3499474
Title
An Improved DM Algorithm Based on Rough Set Theory
Author
Yang Zu-Qiao ; Xiao Xiao-Hong ; Gao Han-ping
Author_Institution
Sch. of Comput. Sci. & Technol., HuangGang Normal Univ., Huanggang
fYear
2007
fDate
21-25 Sept. 2007
Firstpage
3097
Lastpage
3100
Abstract
The basic idea of an improved algorithm is outlined in this paper firstly, includes main steps and the advantages and disadvantages of CART algorithm; and then the definitions of attribute importance and the system comprehensive information entropy and the algorithm of maintaining maximum system comprehensive information entropy are presented. Compares to some disadvantages of CART algorithm such as low computation efficiency of extraction rules and long rule length, the improved algorithm has effect in the experimental result.
Keywords
data mining; entropy; rough set theory; CART algorithm; attribute importance; data mining; improved DM algorithm; maximum system comprehensive information entropy; rough set theory; Computer science; Data mining; Decision trees; Delta modulation; Erbium; Information entropy; Information systems; Neural networks; Rail to rail inputs; Set theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Wireless Communications, Networking and Mobile Computing, 2007. WiCom 2007. International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4244-1311-9
Type
conf
DOI
10.1109/WICOM.2007.769
Filename
4340544
Link To Document