DocumentCode
2144534
Title
A Unified Paradigm for the Accuracy of Classification Based on Granular Computing
Author
Chen, Yongbing ; Liu, Shuang ; Ye, Ping
Author_Institution
Sch. of Math. & Inf. Sci., Zhejiang Normal Univ., Jinhua, China
fYear
2010
fDate
14-16 Aug. 2010
Firstpage
669
Lastpage
672
Abstract
Accuracy is a very important criterion for the classifier in the process of classification. In this paper, a unified paradigm for the calculation of accuracy evaluated different classifier, using topological covering-based granular computing, is presented under the given sample space and different ideal classification assumptions. And corresponding examples for the calculation of accuracy in different classification situations are given.
Keywords
decision trees; pattern classification; accuracy calculation; ideal classification assumption; topological covering-based granular computing; unified paradigm; Accuracy; Conferences; Data mining; Estimation; Prediction methods; Rough sets; accuracy; classification; classifier; covering; granular computing;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing (GrC), 2010 IEEE International Conference on
Conference_Location
San Jose, CA
Print_ISBN
978-1-4244-7964-1
Type
conf
DOI
10.1109/GrC.2010.34
Filename
5576030
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