• 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