ISSN 2394-5125
 

Research Article 


PERFORMANCE ENHANCEMENT OF CREDIT CARD FRAUD DETECTION USING ENHANCED RANDOM TREE-BASED RANDOM FOREST ALGORITHM

V. SUDHEER GOUD, Prof. P. PREMCHAND.

Abstract
Credit card fraud transactions take place regularly and then result in large financial losses. The number of online
activities has increased in high quantities, and online credit card transactions contain an extensive share of these transactions.
Therefore, banks and commercial organizations allow credit card fraud detection purposes, much importance, and interest.
Deceitful transactions can happen in different ways and can be placed into separate sections. Criminals can apply some
methods such as Trojan or Phishing, to borrow data from different people's credit cards. Accordingly, an efficient fraud
detection system is important because it can recognize fraud in time during a criminal employs a borrowed card to utilize.
Generally, credit card fraud movements can appear in both online and offline. But in today's society, online fraud transaction
activities are increasing day by day. So in order to find online fraud transactions, various methods have been used in the
existing system. This paper focuses on four main fraud occasions in real-world operations. Each fraud is addressed using a
series of Text mining models, and the best method is selected via an evaluation. Further, this paper proposes an enhanced
random tree-based random forest algorithm (ERFA) for finding the fraudulent transactions and the accuracy of those
transactions. This algorithm is based on a supervised learning algorithm where it uses decision trees for classification of the
dataset.

Key words: credit card fraud detection, Text mining, enhanced random forest algorithm,


 
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Pubmed Style

V. SUDHEER GOUD, Prof. P. PREMCHAND. PERFORMANCE ENHANCEMENT OF CREDIT CARD FRAUD DETECTION USING ENHANCED RANDOM TREE-BASED RANDOM FOREST ALGORITHM. JCR. 2020; 7(9): 2408-2415. doi:10.31838/jcr.07.09.389


Web Style

V. SUDHEER GOUD, Prof. P. PREMCHAND. PERFORMANCE ENHANCEMENT OF CREDIT CARD FRAUD DETECTION USING ENHANCED RANDOM TREE-BASED RANDOM FOREST ALGORITHM. http://www.jcreview.com/?mno=107472 [Access: May 30, 2021]. doi:10.31838/jcr.07.09.389


AMA (American Medical Association) Style

V. SUDHEER GOUD, Prof. P. PREMCHAND. PERFORMANCE ENHANCEMENT OF CREDIT CARD FRAUD DETECTION USING ENHANCED RANDOM TREE-BASED RANDOM FOREST ALGORITHM. JCR. 2020; 7(9): 2408-2415. doi:10.31838/jcr.07.09.389



Vancouver/ICMJE Style

V. SUDHEER GOUD, Prof. P. PREMCHAND. PERFORMANCE ENHANCEMENT OF CREDIT CARD FRAUD DETECTION USING ENHANCED RANDOM TREE-BASED RANDOM FOREST ALGORITHM. JCR. (2020), [cited May 30, 2021]; 7(9): 2408-2415. doi:10.31838/jcr.07.09.389



Harvard Style

V. SUDHEER GOUD, Prof. P. PREMCHAND (2020) PERFORMANCE ENHANCEMENT OF CREDIT CARD FRAUD DETECTION USING ENHANCED RANDOM TREE-BASED RANDOM FOREST ALGORITHM. JCR, 7 (9), 2408-2415. doi:10.31838/jcr.07.09.389



Turabian Style

V. SUDHEER GOUD, Prof. P. PREMCHAND. 2020. PERFORMANCE ENHANCEMENT OF CREDIT CARD FRAUD DETECTION USING ENHANCED RANDOM TREE-BASED RANDOM FOREST ALGORITHM. Journal of Critical Reviews, 7 (9), 2408-2415. doi:10.31838/jcr.07.09.389



Chicago Style

V. SUDHEER GOUD, Prof. P. PREMCHAND. "PERFORMANCE ENHANCEMENT OF CREDIT CARD FRAUD DETECTION USING ENHANCED RANDOM TREE-BASED RANDOM FOREST ALGORITHM." Journal of Critical Reviews 7 (2020), 2408-2415. doi:10.31838/jcr.07.09.389



MLA (The Modern Language Association) Style

V. SUDHEER GOUD, Prof. P. PREMCHAND. "PERFORMANCE ENHANCEMENT OF CREDIT CARD FRAUD DETECTION USING ENHANCED RANDOM TREE-BASED RANDOM FOREST ALGORITHM." Journal of Critical Reviews 7.9 (2020), 2408-2415. Print. doi:10.31838/jcr.07.09.389



APA (American Psychological Association) Style

V. SUDHEER GOUD, Prof. P. PREMCHAND (2020) PERFORMANCE ENHANCEMENT OF CREDIT CARD FRAUD DETECTION USING ENHANCED RANDOM TREE-BASED RANDOM FOREST ALGORITHM. Journal of Critical Reviews, 7 (9), 2408-2415. doi:10.31838/jcr.07.09.389