EXECUTION OF ASSOCIATION RULE MINING WITH DATA GRIDS IN WEKA 3.8

Kirti Rathi, Dr. Kanwal Garg

Abstract


The premise of this paper is to discover frequent patterns by the use of data grids in WEKA 3.8 environment. Workload imbalance occurs due to the dynamic nature of the grid computing hence data grids are used for the creation and validation of data. Association rules are used to extract the useful information from the large database. In this paper the researcher generate the best rules by using WEKA 3.8 for better performance. WEKA 3.8 is used to accomplish best rules and implementation of various algorithms.

Keywords


Grid Computing, Association Rule Mining, Apriori Algorithm, WEKA 3.8, Visualization tools.

Full Text:

PDF

References


Anuradha Sharma , Seema verma,” Survey Report on Load balancing in Grid Computing environment,” International journal of Advanced Research & Studies, Vol 4, No. 2, Jan- March, 2015.

Frederic Magoules, Thi-MAI-houng Nguyen and Lei Yu, Grid Resource Management toward virtual and services complaint grid computing, CRC, press Taylor & Francis Group(2009).

M.J Zaki ,” Parallel and Distributed Association Mining, a Survey : IEEE Concurrency, 7(4), pp- 4-25, 1999.

Kumar V, Karypis G. and Han E,” Scalable Parallel Data Mining for Association Rules,” IEEE Transactions on data knowledge and engineering, Vol 12, No. 3, pp-337-352, 2000.

R. Agarwal and R. Srikant,” Fast algorithms for mining Association Rules in Large Databases,” International Conference on very large databases, 1994.

P. Tanna and D. Y. Ghodsara,” Using Apriori with Weka for Frequent Pattern Mining ,” International Journal of Trends and Technology, Vol. 12, 2014.

Michael Hahsler and Sudheer chelluboina,” Visualizing Association Rules in Hierarchical Groups “, 42nd Symposium on the interface: Statistical, machine learning, and Visualization Algorithms (Interface 2011).

K.R. Swamy and G. H Babu,” Identification of Frequent Item Search Patterns Using Apriori Algorithm and WEKA Tool”, International Journal of Innovative Technology and Research, Vol. 3, No. 5, pp. 2401-2403, 2015.


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.