Fuel Sales Forecasting with SARIMA-GARCH and Rolling Window
Volume-5 | Issue-3

An Accurate Bitcoin Price Prediction using logistic regression with LSTM Machine Learning model
Volume-3 | Issue-3

A Comprehensive Review on Advanced Driver Assistance System
Volume-4 | Issue-2

Nepali Image Captioning: Generating Coherent Paragraph-Length Descriptions Using Transformer
Volume-6 | Issue-1

A Novel Approach based on PSO and Coloured Petri Net for improving Services in the Emergency Department
Volume-5 | Issue-1

Credit Risk Analysis using Explainable Artificial Intelligence
Volume-6 | Issue-3

Implications of Tokenizers in BERT Model for Low-Resource Indian Language
Volume-4 | Issue-4

Design of Distribution Transformer Health Management System using IoT Sensors
Volume-3 | Issue-3

Cloud Load Estimation with Deep Logarithmic Network for Workload and Time Series Optimization
Volume-3 | Issue-3

Energy Management System in the Vehicles using Three Level Neuro Fuzzy Logic
Volume-3 | Issue-3

An Integrated Approach for Crop Production Analysis from Geographic Information System Data using SqueezeNet
Volume-3 | Issue-4

An Accurate Bitcoin Price Prediction using logistic regression with LSTM Machine Learning model
Volume-3 | Issue-3

Design of Distribution Transformer Health Management System using IoT Sensors
Volume-3 | Issue-3

Design of a Food Recommendation System using ADNet algorithm on a Hybrid Data Mining Process
Volume-3 | Issue-4

Automatic Diagnosis of Alzheimer’s disease using Hybrid Model and CNN
Volume-3 | Issue-4

Effective Prediction of Online Reviews for Improvement of Customer Recommendation Services by Hybrid Classification Approach
Volume-3 | Issue-4

Acoustic Features Based Emotional Speech Signal Categorization by Advanced Linear Discriminator Analysis
Volume-3 | Issue-4

Analysis of Statistical Trends of Future Air Pollutants for Accurate Prediction
Volume-3 | Issue-4

Identification of Electricity Threat and Performance Analysis using LSTM and RUSBoost Methodology
Volume-3 | Issue-4

Review on Data Securing Techniques for Internet of Medical Things
Volume-3 | Issue-3

Home / Archives / Volume-6 / Issue-4 / Article-5

Volume - 6 | Issue - 4 | december 2024

Performance Analysis of Machine Learning Techniques in Credit Card Fraud Detection Open Access
Suganya I  , Naveen K., Ragul P., Sangeeth M.  118
Pages: 390-400
Cite this article
I, Suganya, Naveen K., Ragul P., and Sangeeth M.. "Performance Analysis of Machine Learning Techniques in Credit Card Fraud Detection." Journal of Soft Computing Paradigm 6, no. 4 (2024): 390-400
Published
07 February, 2025
Abstract

The rapid growth of e-commerce and online banking has resulted in a substantial rise in credit card fraud incidents. Consequently, machine learning and advanced deep learning techniques have emerged as critical solutions. This study integrates the findings of a few researchers, examining diverse methodologies, including Naïve Bayes, K-Nearest Neighbor (KNN), Logistic Regression, CNN, RNN, and ensemble learning. A comparative performance analysis, emphasizing the challenges posed by imbalanced datasets, demonstrates the superior performance of hybrid models, in enhancing the accuracy of detecting the fraudulent in credit card transactions.

Keywords

Credit Card Fraud Detection Machine Learning deep learning Online Banking Security Fraud Prevention

×

Currently, subscription is the only source of revenue. The subscription resource covers the operating expenses such as web presence, online version, pre-press preparations, and staff wages.

To access the full PDF, please complete the payment process.

Subscription Details

Category Fee
Article Access Charge
15 USD
Open Access Fee Nil
Annual Subscription Fee
200 USD
After payment,
please send an email to irojournals.contact@gmail.com / journals@iroglobal.com requesting article access.
Subscription form: click here