Credit Card Fraud Detection Using Weighted Support Vector Machine

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Applied Mathematics

ISSN Print: 2152-7385
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"Credit Card Fraud Detection Using Weighted Support Vector Machine"
written by Dongfang Zhang, Basu Bhandari, Dennis Black,
published by Applied Mathematics, Vol.11 No.12, 2020

has been cited by the following article(s):

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[1]	Improving the accuracy of predicting the cybercrime using novel random forest algorithm over support vector machine
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[2]	Fraud Detection using Machine Learning
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[3]	K‐Fuse: Credit card fraud detection based on a classification method with a priori class partitioning and a novel feature selection strategy
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[4]	Detection of credit card fraud through machine learning in banking industry
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[5]	A Comparison of Logistic Regression Classifier and Random Forest Classifier for the Accurate Classification of Credit Card Fraudulent Transactions
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[6]	Community Clustering on Fraud Transactions Applied the Louvain-Coloring Algorithm
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[7]	DEVELOPMENT OF HEALTH INSURANCE CLAIM PREDICTION METHOD BASED ON SUPPORT VECTOR MACHINE AND BAT ALGORITHM
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[11]	A systematic review of literature on credit card cyber fraud detection using machine and deep learning
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[12]	Sentiment analysis in detecting sophistication and degradation cues in malicious web contents
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[13]	DeLClustE: Protecting Users from Credit-Card Fraud Transaction via the Deep-Learning Cluster Ensemble
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[14]	DeGATraMoNN: Deep Learning Memetic Ensemble to Detect Spam Threats via a Content-Based Processing
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[15]	Forging a user-trust hybrid memetic modular neural network card fraud detection ensemble: A Pilot study
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[16]	Chinese corporate fraud risk assessment with machine learning
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[17]	Health claim insurance prediction using support vector machine with particle swarm optimization
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[18]	An optimal approach for fraud detection by comparing random forest algorithm and support vector machine algorithm for credit card transaction with improved …
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[19]	An Innovative Sensing Machine Learning Technique to Detect Credit Card Frauds in Wireless Communications
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[20]	Research Article An Innovative Sensing Machine Learning Technique to Detect Credit Card Frauds in Wireless Communications
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[21]	Managing credit risk and the cost of equity with machine learning techniques
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[22]	Yeniden Örnekleme Metotlarının Kredi Kartı Sahtecilik Tespiti için Topluluk Öğrenmesine Kapsamlı Analizi
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[23]	A new feature engineering framework for financial cyber fraud detection using machine learning and deep learning
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[24]	A Review of Credit Card Fraud Detection Using Machine Learning Algorithms
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[1]	Enhancing fraud detection in the Ethereum blockchain using ensemble learning PeerJ Computer Science, 2025 DOI:10.7717/peerj-cs.2716

[2]	Improving the accuracy of predicting the cybercrime using novel random forest algorithm over support vector machine FIFTH INTERNATIONAL CONFERENCE ON APPLIED SCIENCES: ICAS2023, 2024 DOI:10.1063/5.0197500

[3]	Credit Card Fraud Detection Method Based on KRSMOTE+ENN and XGBoost Algorithm Proceedings of the 5th International Conference on Computer Information and Big Data Applications, 2024 DOI:10.1145/3671151.3671365

[4]	K‐Fuse: Credit card fraud detection based on a classification method with a priori class partitioning and a novel feature selection strategy Applied Stochastic Models in Business and Industry, 2024 DOI:10.1002/asmb.2868

[5]	Advancing Model Performance With ADASYN and Recurrent Feature Elimination and Cross-Validation in Machine Learning-Assisted Credit Card Fraud Detection: A Comparative Analysis IEEE Access, 2024 DOI:10.1109/ACCESS.2024.3457922

[6]	Building Business Models with Machine Learning Advances in Systems Analysis, Software Engineering, and High Performance Computing, 2024 DOI:10.4018/979-8-3693-3884-1.ch001

[7]	Enhancing Performance of Financial Fraud Detection Through Machine Learning Model SSRN Electronic Journal, 2024 DOI:10.2139/ssrn.4980350

[8]	International Conference on Innovative Computing and Communications Lecture Notes in Networks and Systems, 2023 DOI:10.1007/978-981-19-3679-1_52

[9]	A systematic review of literature on credit card cyber fraud detection using machine and deep learning PeerJ Computer Science, 2023 DOI:10.7717/peerj-cs.1278

[10]	Vehicle pattern recognition in a novel way using KNN and compare prediction accuracy with CNN algorithm CONTEMPORARY INNOVATIONS IN ENGINEERING AND MANAGEMENT, 2023 DOI:10.1063/5.0177012

[11]	An optimal approach for fraud detection by comparing random forest algorithm and support vector machine algorithm for credit card transaction with improved accuracy CONTEMPORARY INNOVATIONS IN ENGINEERING AND MANAGEMENT, 2023 DOI:10.1063/5.0177045

[12]	Chinese corporate fraud risk assessment with machine learning Intelligent Systems with Applications, 2023 DOI:10.1016/j.iswa.2023.200294

[13]	An Innovative Sensing Machine Learning Technique to Detect Credit Card Frauds in Wireless Communications Wireless Communications and Mobile Computing, 2022 DOI:10.1155/2022/2439205

[14]	Comprehensive Analysis of Resampling Methods on Ensemble Learning for Credit Card Fraud Detection Afyon Kocatepe University Journal of Sciences and Engineering, 2022 DOI:10.35414/akufemubid.1066453

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