Title :
Association Rules Mining Based on the Improved Immune Algorithm
Author :
Zhang, Yongqiang ; Bu, Shuyang ; Zhang, Yongjian
Author_Institution :
Hebei Univ. of Eng., Handan, China
Abstract :
Firstly, in this paper we propose an improved immune algorithm, that is, introduce the Metropolis criterion into the selection operation of immune algorithm, and the Metropolis immune algorithm (MIA) is formed, then we carry out the theoretical analysis and experimental simulation aiming at the performance of the MIA; secondly, we use this algorithm to excavate association rules, and propose a new algorithm of association rule mining, then we can verify that the algorithm is feasible and effective through theoretical analysis and experimental results.
Keywords :
artificial immune systems; data mining; database management systems; transaction processing; Metropolis immune algorithm; association rules mining; selection operation; transaction database; Algorithm design and analysis; Association rules; Biology computing; Convergence; Data mining; Immune system; Machine learning algorithms; Performance analysis; Random number generation; Simulated annealing; Association rule mining; Immune algorithm; MIA; Metropolis criterion;
Conference_Titel :
Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on
Conference_Location :
Nanchang
Print_ISBN :
978-0-7695-3859-4
DOI :
10.1109/IITA.2009.260
