文章基本信息

标题：Distance Weight Optimization of Association Rule Mining with Improved Genetic Algorithm
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作者：Nikhil Jain ; Vishal Sharma
期刊名称：International Journal of Electrical, Electronics and Computer Engineering
电子版ISSN：2277-2626
出版年度：2012
卷号：1
期号：2
页码：3
语种：English
出版社：RESEARCH TREND
摘要：ABSTRACT : In this paper, the main area of concentration was to optimize the rules generated by Association Rule Mining (apriori method), using Genetic Algorithms. 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. The main motivation for using GAs in the discovery of high-level prediction rules is that they perform a global search and cope better with attribute interaction than the greedy rule induction algorithms often used in data mining. The improvements applied in GAs are definitely going to help the rule based systems used for classification as described in results and conclusions.