Academic Journals Database
Disseminating quality controlled scientific knowledge

Optimized association rule mining using genetic algorithm

ADD TO MY LIST
 
Author(s): Anandhavalli M. | Suraj Kumar Sudhanshu | Ayush Kumar | Ghose M.K.

Journal: Advances in Information Mining
ISSN 0975-3265

Volume: 1;
Issue: 2;
Start page: 01;
Date: 2009;
VIEW PDF   PDF DOWNLOAD PDF   Download PDF Original page

Keywords: Genetic Algorithm (GA) | Association Rules | Support | Confidence | Data Mining

ABSTRACT
In general the rule generated by association rule mining algorithms like priori, partition,pincer-search, incremental, border algorithm etc, does not consider negation occurrence of the attributein them and also these rules have only one attribute in the consequent part. By using Genetic Algorithm(GAs) the system can predict the rules which contain negative attributes in the generated rules alongwith more than one attribute in consequent part. The major advantage of using GAs in the discovery ofprediction rules is that they perform global search and its complexity is less compared to otheralgorithms as the genetic algorithm is based on the greedy approach. The main aim of this paper is tofind all the possible optimized rules from given data set using genetic algorithm.
RPA Switzerland

RPA Switzerland

Robotic process automation

    

Tango Rapperswil
Tango Rapperswil