International Journal of Soft Computing

124
Views

0
Downloads

GA Optimized Negative Association Rule Mining

Sanjeev Sharma , Sudhir Sharma and Jitendra Agrawal
Page: 124-128 | Received 21 Sep 2022, Published online: 21 Sep 2022

By Research Area

Medicine & Public Health Life Sciences Engineering Mathematics Biomedicine Physics Chemistry Computer Science Earth Sciences Social Sciences Business and Management Psychology Materials Science Economics Education Environment Philosophy Statistics Law Political Science and International Relations Pharmacy Dentistry Energy Linguistics Geography Finance Criminology and Criminal Justice Medicine Cultural and Media Studies History Architecture / Design Literature Biomedical Sciences Religious Studies Education & Language Food Science & Nutrition Public Health

By Volume and Issue

Abstract

This study discusses the use of genetic algorithm in mining negative association rules. In general the rule generated by Association Rule Mining technique do not consider the negative occurrences of attributes in them, but by using Genetic Algorithms (GAs) over these rules the system can predict the rules which contains negative attributes. GA is used for this kind of knowledge discovery because of their ability to search globally and perform well in case of attributes interaction. Their strength is essentially due to updating of the whole population, consisting of normal case of individuals and worst case of individuals of the possible solution in an adaptive way.

How to cite this article:

Sanjeev Sharma , Sudhir Sharma and Jitendra Agrawal . GA Optimized Negative Association Rule Mining.
DOI: https://doi.org/10.36478/ijscomp.2007.124.128
URL: https://www.makhillpublications.co/view-article/1816-9503/ijscomp.2007.124.128