Building Fuzzy Associative Classifier Using Fuzzy Values
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 109 | Views: 399

Research Paper | Computer Science & Engineering | India | Volume 3 Issue 7, July 2014 | Popularity: 6.6 / 10


     

Building Fuzzy Associative Classifier Using Fuzzy Values

P. Kayal, S. Kannan


Abstract: Association rule mining is a popular and well researched method for discovering interesting relations between variables in large databases. Classification based on association rules is considered to be an effective and beneficial approach. However, mining the domain of quantitative attributes leads to a common existing sharp boundary problem. This can be over-ruled by the use of fuzziness in the variables and the association rule mining. This paper aims at proposing a classification based on fuzzy association rule mining called Fuzzy Associative Classifier (FAC) to predict the level of work-force leadership qualities.


Keywords: Fuzzification, Partitioning, Associative classifier, Fuzzy weight, Skill level


Edition: Volume 3 Issue 7, July 2014


Pages: 1498 - 1500



Please Disable the Pop-Up Blocker of Web Browser

Verification Code will appear in 2 Seconds ... Wait



Text copied to Clipboard!
P. Kayal, S. Kannan, "Building Fuzzy Associative Classifier Using Fuzzy Values", International Journal of Science and Research (IJSR), Volume 3 Issue 7, July 2014, pp. 1498-1500, https://www.ijsr.net/getabstract.php?paperid=201412371, DOI: https://www.doi.org/10.21275/201412371

Top