Open AccessA Performance Analysis of Detecting Credit Card Fraud by using CT18 Method
Author(s) -
S. Subbulakshmi,
Dr.D.J. Evanjaline
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d5280.118419
Subject(s) - credit card , payment , credit card fraud , database transaction , purchasing , business , harm , suspect , lease , computer science , computer security , actuarial science , finance , database , marketing , political science , law
Credit cards are a significant component of everyday life. Whether purchasing gas and supermarket stores or reserving a hotel and lease a car for the next holiday. Credit cards are a pleasant and safe type of client payment. Advantages that differ from harm security on payments to the convenience of disputing suspect fees or suspicious activity make credit cards such an appealing form of transaction. It takes an hour for any time activities, online shopping, and paperless system. As the amount of credit card customers rises day by day, significant illegal activities eventually enhance. CT18 technique is the procedure for categorizing information directed at reformatting observations into CT18, whereby each observation belongs to the closest mean cluster. This is one of the simplest unsupervised learning algorithms that solve the well-known grouping problem