Download Rough Set Approach to Rule Induction Mining

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.
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