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 :
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