Support vector machine with information gain based classification for credit card fraud detection system
Joint Authors
Kumar, Dhananjay
Poongodi, Kannan
Source
The International Arab Journal of Information Technology
Issue
Vol. 18, Issue 2 (31 Mar. 2021), pp.199-207, 9 p.
Publisher
Zarqa University Deanship of Scientific Research
Publication Date
2021-03-31
Country of Publication
Jordan
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Abstract EN
In the credit card industry, fraud is one of the major issues to handle as sometimes the genuine credit card customers may get misclassified as fraudulent and vice-versa.
Several detection systems have been developed but the complexity of these systems along with accuracy and precision limits its usefulness in fraud detection applications.
In this paper, a new methodology Support Vector Machine with Information Gain (SVMIG) to improve the accuracy of identifying the fraudulent transactions with high true positive rate for the detection of frauds in credit card is proposed.
In SVMIG, the min-max normalization is used to normalize the attributes and the feature set of the attributes are reduced by using information gain based attribute selection.
Further, the Apriori algorithm is used to select the frequent attribute set and to reduce the candidate’s itemset size while detecting fraud.
The experimental results suggest that the proposed algorithm achieves 94.102% higher accuracy on the standard dataset compared to the existing Bayesian and random forest based approaches for a large sample size in dealing with legal and fraudulent transactions.
American Psychological Association (APA)
Poongodi, Kannan& Kumar, Dhananjay. 2021. Support vector machine with information gain based classification for credit card fraud detection system. The International Arab Journal of Information Technology،Vol. 18, no. 2, pp.199-207.
https://search.emarefa.net/detail/BIM-1430912
Modern Language Association (MLA)
Poongodi, Kannan& Kumar, Dhananjay. Support vector machine with information gain based classification for credit card fraud detection system. The International Arab Journal of Information Technology Vol. 18, no. 2 (Mar. 2021), pp.199-207.
https://search.emarefa.net/detail/BIM-1430912
American Medical Association (AMA)
Poongodi, Kannan& Kumar, Dhananjay. Support vector machine with information gain based classification for credit card fraud detection system. The International Arab Journal of Information Technology. 2021. Vol. 18, no. 2, pp.199-207.
https://search.emarefa.net/detail/BIM-1430912
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 205-206
Record ID
BIM-1430912