Prevention of Post-Operative Wound Infection in Accordance with Evidence Based Practice

Archana Maurya, Seema Mendhe

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

How to Cite?: Archana Maurya, Seema Mendhe, "Prevention of Post-Operative Wound Infection in Accordance with Evidence Based Practice", Volume 3 Issue 7, July 2014, International Journal of Science and Research (IJSR), Pages: 1173-1177, https://www.ijsr.net/getabstract.php?paperid=20141237, DOI: https://dx.doi.org/10.21275/20141237

Download Citation: APA | MLA | BibTeX | EndNote | RefMan