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Classifying Association Rules with Minimized Sets using Fuzzy-Aprioi Algorithm
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 128 - Number 5 |
| Year of Publication: 2015 |
| Authors: Sonam Jain, Anand Rajawat |
10.5120/ijca2015906560
|
Sonam Jain, Anand Rajawat . Classifying Association Rules with Minimized Sets using Fuzzy-Aprioi Algorithm. International Journal of Computer Applications. 128, 5 ( October 2015), 41-47. DOI=10.5120/ijca2015906560
Abstract
Using Association Rule mining is extremely well-organized method for getting strong relation between correlated data or information. The correlation of data provides significance complete taking out progression. For the mining of positive and negative rules, a range of algorithms are utilized for example Apriori algorithm and tree based algorithm. A numeral of algorithms is be unsure presentation but manufactures huge number of negative association rule and also goes through from multi-scan difficulty. The proposal of is to get rid of these difficulties and decrease huge amount of negative rules. Here an efficient technique is implemented for the classification of association rules generated using Fuzzy-Apriori algorithm and classification of these rules can be done supervised learning such as Naïve Bayes Algorithm. The proposed methodology implemented here provides efficient results as compared to the existing technique implemented for the generation of association rules.
References
- Idheba Mohamad Ali O. Swesi, Azuraliza Abu Bakar, Anis Suhailis Abdul Kadir “Mining Positive and Negative Association Rules from Interesting Frequent and Infrequent Itemsets”, 9th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2012), pp. 650 – 655, 2012.
- A. K. Santra, and S. Jayasudha “Classification of Web Log Data to Identify Interested Users Using Naïve Bayesian Classification”, International Journal of Computer Science Issues (IJCSI), Vol. 9, Issue 1, No 2, January 2012.
- Pengfei Guo, Xuezhi Wang and Yingshi Han “The Enhanced Genetic Algorithms for the Optimization Design”, 3rd International Conference on Biomedical Engineering and Informatics (BMEI), Vol. 7, pp. 2990 – 2994, 2010.
- Xin Li, Xuefeng Zheng, Jingchun Li, and Shaojie Wang “Frequent Itemsets Mining in Network Traffic Data”, Fifth International Conference on Intelligent Computation Technology and Automation, pp. 394- 397, 2012.
- Soumadip Ghosh, Sushanta Biswas, Debasree Sarkar, Partha Pratim Sarkar “Mining Frequent Itemsets Using Genetic Algorithm”, International Journal of Artificial Intelligence & Applications (IJAIA), Vol.1, No.4, pp. 133 – 143, October 2010.
- Agrawal R., Imielinski T. and Swami A. “Mining Association rules between sets of items in large databases, In the Proc. of the ACM SIGMOD Int’l Conf. on Management of Data (ACM SIGMOD ‘93), pp. 207-216, Washington, USA,1993.
- G. Vijay Bhasker, K. Chandra Shekar, V. Lakshmi Chaitanya “Mining Frequent Itemsets for Non Binary Data Set Using Genetic Algorithm”, International Journal Of Advanced Engineering Sciences And Technologies (IJAEST), ISSN: 2230-7818, Vol. 11, Issue No. 1, pp. 143 – 152, 2011.
- G. Sathyadevi, “Application of cart algorithm in Hepatitis disease diagnosis”, IEEE International Conference on Recent Trends in Information Technology (ICRTIT-2011), pp. 1283 - 1287, June 2011.
- S. Vijayalakshmi, Dr. V.Mohan, M. S. Sassirekha, O.R. Deepika, “Extracting Sequential Access Pattern from Pre-processed Web Logs”, Proceeding in IEEE International Conference on Process Automation, Control and Computing (PACC-2011), pp. 1- 6, 2011.
- Alka Gangrade, Durgesh Kumar Mishra and Ravindra Patel ,“Classification Rule Mining through SMC for Preserving Privacy Data Mining: A Review”, International Conference on Machine Learning and Computing IPCSIT, vol. 3, pp. 431- 434, IACSIT Press Singapore, 2011.
- HidenaoAbe“DevelopmentofaClassificationRuleMiningFramework by Using Temporal Pattern Extraction”, New fundamental technologies in data mining, pp. 493-504, January 2011.
- Farah Hanna AL-Zawaidah, Yosef Hasan Jbara and Marwan AL-Abed Abu-Zanona “An Improved Algorithm for Mining Association Rules in Large Databases”, World of Computer Science and Information Technology Journal (WCSIT), ISSN: 2221-0741, Vol. 1, No. 7, pp. 311-316, 2011.
- Ruchi Bhargava and Shrikant Lade “Effective Positive Negative Association Rule Mining Using Improved Frequent Pattern”, International Journal of Modern Engineering Research (IJMER), ISSN: 2249-6645, Vol.3, Issue.2, pp-1256-1262, March-April. 2013.
- Luca Cagliero and Paolo Garza “Infrequent Weighted Itemset Mining using Frequent Pattern Growth”, IEEE Transactions on Knowledge and Data Engineering, pp. 1- 14, 2013.
- R. Uday Kiran and P. Krishna Reddy “Novel Techniques to Reduce Search Space in Multiple Minimum Supports-Based Frequent Pattern Mining Algorithms”, Proceedings of the 14th International Conference on Extending Database Technology, pp. 11 – 20, 2011.
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