DocumentCode
623112
Title
Comparison of algorithms for computing data set reducts
Author
Tomasz, Kanik
Author_Institution
Dept. of Math. Methods, Univ. of Zilina, Zilina, Slovakia
fYear
2013
fDate
29-31 May 2013
Firstpage
99
Lastpage
103
Abstract
This paper compare four different algorithms for computing reducts or a reduct approximations based on Rough Set Theory. Reducts are used to create rule sets and then to classification of the test set. The data of patients suffering from heart disease is used to make algorithm´s accuracy measure and create Receiver Operating Characteristic (ROC) curves. It has been concluded that out of these four methods of reduct calculation, classification through table rule set using covering algorithm yields best accuracy. Moreover statistical methods for algorithms comparison are presented. The ROSSETA software is used for reduct generation, rule set calculation and rough set classification. The R software environment is used for statistical computing and graphics generation.
Keywords
approximation theory; pattern classification; rough set theory; ROC curve; ROSSETA software; algorithm comparison; covering algorithm; data classification; data set reduct; graphics generation; heart disease patient; receiver operating characteristic curve; reduct approximation; reduct calculation method; reduct generation; rough set classification; rough set theory; rule set calculation; statistical computing; Accuracy; Algorithm design and analysis; Approximation algorithms; Approximation methods; Genetics; Information systems; Receivers; Accuracy measure; R project; ROSSETA; Reduct calculation; Rough Set Theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Digital Technologies (DT), 2013 International Conference on
Conference_Location
Zilina
Print_ISBN
978-1-4799-0923-0
Type
conf
DOI
10.1109/DT.2013.6566295
Filename
6566295
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