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Asian Research Consortium Asian Journal of Research in Social Sciences and Humanities Vol. 6, No. 9, September 2016, pp. 100-114. Asian Journal of Research in Social Sciences and Humanities ISSN 2249-7315 A Journal Indexed in Indian Citation Index www.aijsh.com DOI NUMBER: 10.5958/2249-7315.2016.00781.4 Category:Science and Technology Rough Set Approach to Rule Induction Mining D. Shanthi*; S. Vengataasalam** *Department of Mathematics, Kongu Polytechnic College, Perundurai, Tamilnadu, India. **Department of Mathematics, Kongu Polytechnic College, Perundurai, Tamilnadu, India. Abstract Extracting useful patterns is an important theme in data mining. Fuzzy logic and Rough sets are the most common techniques applied in data mining problems where rule sets are used to classify new cases. In order to extract minimum rules with high data coverage and fast processing time based on rule induction. This paper presents a hybrid method called, Updating Induction of Decision Rules based on Fuzzy Rough Set (UIDR-FRS). The UIDR-FRS method is based on the integration of fuzzy logic and rough sets and hence constructs a novel rule extraction model. The attribute reduction algorithm using fuzzy logic and rules extraction method based on rough sets are proposed. The attributes of decision table are analyzed using fuzzy logic and subsequently a rule extraction model based on these attributes is built through integration of rough sets and fuzzy logic model. Experiments on real-life data sets are conducted to test and verify the validity of the proposed measure. Applications of the proposed rule induction in rule extraction and accuracy are also studied with experiments. Extensive experimental results verify the effectiveness and efficiency of the attribute reduction algorithms for a compacted decision table. Keywords: Rough sets, Fuzzy logic, Data Mining, Decision Rules, Attribute Reduction, Rule Extraction. 100 Shanthi & Vengataasalam (2016). Asian Journal of Research in Social Sciences and Humanities, Vol. 6, No.9, pp. 100-114. References Abbasi, A,F. France, Z. Zhang & H.Chen (2011): Selecting Attributes forSentiment Classification Using Feature Relation Networks, IEEE Transactions onKnowledge and Data Engineering, Vol. 23, No. 3 Chen, H, T. Li, C. Luo, Shi-Jinn Horng& G. Wang(2014): A Rough Set-Based Method for Updating Decision Rules on Attribute Values Coarsening and Refining, IEEE Transactions on Knowledge and Data Engineering, Vol. 26, No. 12 Chen, H, T. Li, C. Luo, Shi-Jinn Horng & G. 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