UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 7 Issue 5
May-2020
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRDV06024


Registration ID:
231856

Page Number

104-110

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Title

Credit Card Fraud detection using Machine Learning Models

Abstract

Due to increase of fraud which results in loss of money across the globe, several methodologies and techniques developed for detecting frauds Fraud detection involves analyzing the activities of users in order to understand the malicious behaviour of users. Malicious behaviour is a broad term including delinquency, fraud, intrusion, and account defaulting. This paper presents a survey of current techniques used in credit card fraud detection and evaluates the machine learning approach to identify fraud detection. In the proposed work, we analyze credit card fraud detection using machine learning algorithm namely K-Nearest Neighbor and Ensemble Model of Random Forest. To make the learning process efficient, we used infinite latent feature selection algorithm for feature selection. The performance of the algorithm is evaluated on various measures like Accuracy, Precision and Recall.

Key Words

Machine learning, Ensemble Model of Random Forest, KNN.

Cite This Article

"Credit Card Fraud detection using Machine Learning Models ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 5, page no.104-110, May-2020, Available :http://www.jetir.org/papers/JETIRDV06024.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Credit Card Fraud detection using Machine Learning Models ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 5, page no. pp104-110, May-2020, Available at : http://www.jetir.org/papers/JETIRDV06024.pdf

Publication Details

Published Paper ID: JETIRDV06024
Registration ID: 231856
Published In: Volume 7 | Issue 5 | Year May-2020
DOI (Digital Object Identifier):
Page No: 104-110
Country: -, -, - .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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