International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Science , Computer Science and Engineering

Volume5,May 2018,

Topic : An Effective model for mutagenesis prediction using Multi-relational Fuzzy Tree

Authors:Dr. C.R.Vijayalakshmi || Dr. P.G Sivagaminathan, Dr.M.Thangaraj

Abstract:Most of the real world applications such as Loan approval, Credit card fraud detection etc uses relational databases which contain multiple relations that are inter-linked with the help of primary and foreign keys. It is very tricky to examine these applications with the help of traditional classification methods such as RIPPER and RIDOR. These methods are suitable for single relation and generate simple and comprehensible rules. But it cannot handle uncertainties and noises present in the real dataset. This paper presents a novel method for generating multi-relational classification model for mutagenesis prediction. The classifier is constructed based on the fuzzy extension of the decision tree. The experimental results show the efficiency of the proposed method compared to the existing algorithms.

Keywords: CrossMine, Multi relational classification, Mutagenesis, target relation, tuple id propagation

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DOI: 01.1617/vol5/iss5/pid17896


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Editor-in-Chief

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Dr. Allon Guez
Professor, Drexel University,
USA


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IMPACT FACTOR: 4.890

ISSN(Online):2394-2320

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Thomson Reuters ID : q-6288-2016.
ORCiD Research ID : 0000-0001-9540-6799

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ACCEPTANCE RATIO: 28.69%
ARTICLES PUBLISHED:0521
PAPER RECEIVED:01730
Journal Code : IJERCSE
Electronic ISSN : 2394-2320
Impact Factor : 4.890
Frequency : monthly
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