Credit Card Fraud Detection using a Combined Approach of Genetic Algorithm and Random Forest

Dr. Jitendra Jaiswal; M. Bhavana Lakshmi Priya

Title:
Credit Card Fraud Detection using a Combined Approach of Genetic Algorithm and Random Forest

Authors:
M. Bhavana Lakshmi Priya | Dr. Jitendra Jaiswal

Cite This Article :

M. Bhavana Lakshmi Priya | Dr. Jitendra Jaiswal "Credit Card Fraud Detection using a Combined Approach of Genetic Algorithm and Random Forest" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-5, August 2020, pp.230-233, URL: https://www.ijtsrd.com/papers/ijtsrd31774.pdf

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Abstract :
Nowadays the companies are growing around the world and a lot of data is also processing daily. This data helps the companies for future business-related purposes for this they will store the data. Is the data is stolen the company will affects it. In this paper, we are discussing credit card fraud detection. Credit card fraud detection is of two types mainly first is through online and second is through the physical card. By stealing the information related to the credit card they can fraud large amounts of money transfer or a large amount of purchase before the cardholder finds out. For detecting the frauds, the companies are using many machine learning techniques for finding transactions that are fraudulent or not. This paper is a combined approach of genetic algorithm and random forest the genetic algorithm is used for feature selection and in the random forest, we used random forest classifiers by splitting the training and testing set. The combination of both gives good results then alone.

Keywords :
Credit Card Fraud Detection, Genetic Algorithm, Random Forest

Publication Details:

Unique Identification Number : IJTSRD31774

Published In : Volume-4 | Issue-5, August 2020

Page Number(s) : 230-233

Publisher Name : IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470

Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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