International Journal of
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Data Mining Approach for Feature Reduction Using Fuzzy Association Rule
Data Mining Approach for Feature Reduction Using Fuzzy Association Rule
Siji P D1 , M.L.Valarmathi 2
1 Department of Computer science, St. Josephs College Irinjalakuda, Thrissur, India.
2 Department of EEE, Alagappa Chettiar College of Engineering and Technology College Road, Thilagar Nagar, India.
Correspondence should be addressed to: srblessy@gmail.com.

Section:Research Paper, Product Type: Journal Paper
Volume-5 , Issue-11 , Page no. 44-50, Nov-2017

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v5i11.4450

Online published on Nov 30, 2017

Copyright © Siji P D, M.L.Valarmathi . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 
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IEEE Style Citation: Siji P D, M.L.Valarmathi, “Data Mining Approach for Feature Reduction Using Fuzzy Association Rule”, International Journal of Computer Sciences and Engineering, Vol.5, Issue.11, pp.44-50, 2017.

MLA Style Citation: Siji P D, M.L.Valarmathi "Data Mining Approach for Feature Reduction Using Fuzzy Association Rule." International Journal of Computer Sciences and Engineering 5.11 (2017): 44-50.

APA Style Citation: Siji P D, M.L.Valarmathi, (2017). Data Mining Approach for Feature Reduction Using Fuzzy Association Rule. International Journal of Computer Sciences and Engineering, 5(11), 44-50.
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Abstract :
Data mining is an upgrading technology for knowledge extraction in many fields like medical, educational, industrial, etc. Extracting an important data from large database is most vital factor. Data extraction processwere done through many techniques like feature extraction, prediction, classification, etc. for our research analyses prediction of data mining helps a lot for accessing useful information. In this paper we focused on road traffic dataset and we used fuzzy data extraction for membership function by using FCM. For the knowledge extraction process here we implemented the correlation and coefficient algorithm for road traffic dataset and attribute reduction were done by using Genetic algorithm and finally with the help of A-Priori algorithm we generate the rule for the mining the associate object for feature reduction.
Key-Words / Index Term :
Data Mining, Prediction, Feature Reduction, Fuzzy, Association Rule and Rule Generation
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