Detection of Credit Card Fraud Using AdaBoost and Majority Voting

International Journal of Innovative Research in Technology

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ISSN: 2349-6002 ESTD Year: 2014

UGC approved journal no 47859

Detection of Credit Card Fraud Using AdaBoost and Majority Voting
Author(s):
Vinutha D, Dr. Mohammed Rafi
Keywords:
credit card, fraud detection, electronic transaction, AdaBoost, majority voting, classification.
Abstract
Credit card is one of the popular modes of payment for electronic transactions. With the developments in the information technology, fraud is spreading all over the world, resulting in huge financial losses. Credit card fraud is a serious and growing problem. In this paper, machine learning algorithms are used to detect credit card fraud. Standard models are used first. Then, hybrid methods which use AdaBoost and majority voting methods are applied. We present detailed experimental results to show the effectiveness of our approach and compare it with other techniques available in the literature. This paper provides a picture of recent trend in credit card fraud detection.
Article Details
Unique Paper ID: 148377 Publication Volume & Issue: Volume 6, Issue 1 Page(s): 937 - 939
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