DocumentCode
1561651
Title
A Classification Approach of Granules Based on Variable Precision Rough Sets
Author
Gu, Shen-Ming ; Wu, Wei-Zhi ; Chen, Hong-Tao
Author_Institution
Zhejiang Ocean Univ., Zhejiang
fYear
2007
Firstpage
163
Lastpage
168
Abstract
The key to granular computing (GrC) is to make use of granules in problem solving. Classification is one of important problems in machine learning and data mining. With view of granular computing, this paper presents a classification approach to granules based on the variable precision rough set (VPRS) model. An algorithm is proposed and a tree structure of granules is given.
Keywords
pattern classification; rough set theory; classification approach; data mining; granular computing; machine learning; variable precision rough sets; Data mining; Information science; Information systems; Mathematics; Oceans; Physics; Problem-solving; Rough sets; Set theory; Tree data structures; Granular computing; granules; variable precision rough sets;
fLanguage
English
Publisher
ieee
Conference_Titel
Cognitive Informatics, 6th IEEE International Conference on
Conference_Location
Lake Tahoo, CA
Print_ISBN
9781-4244-1327-0
Electronic_ISBN
978-1-4244-1328-7
Type
conf
DOI
10.1109/COGINF.2007.4341887
Filename
4341887
Link To Document