[HTML][HTML] Financial fraud: a review of anomaly detection techniques and recent advances
With the rise of technology and the continued economic growth evident in modern society,
acts of fraud have become much more prevalent in the financial industry, costing institutions …
acts of fraud have become much more prevalent in the financial industry, costing institutions …
Outlier detection: Methods, models, and classification
A Boukerche, L Zheng, O Alfandi - ACM Computing Surveys (CSUR), 2020 - dl.acm.org
Over the past decade, we have witnessed an enormous amount of research effort dedicated
to the design of efficient outlier detection techniques while taking into consideration …
to the design of efficient outlier detection techniques while taking into consideration …
A systematic study of the class imbalance problem in convolutional neural networks
In this study, we systematically investigate the impact of class imbalance on classification
performance of convolutional neural networks (CNNs) and compare frequently used …
performance of convolutional neural networks (CNNs) and compare frequently used …
A broad review on class imbalance learning techniques
S Rezvani, X Wang - Applied Soft Computing, 2023 - Elsevier
The imbalanced learning issue is related to the performance of learning algorithms in the
presence of asymmetrical class distribution. Due to the complex characteristics of …
presence of asymmetrical class distribution. Due to the complex characteristics of …
Credit card fraud detection using machine learning techniques: A comparative analysis
JO Awoyemi, AO Adetunmbi… - … and informatics (ICCNI), 2017 - ieeexplore.ieee.org
Financial fraud is an ever growing menace with far consequences in the financial industry.
Data mining had played an imperative role in the detection of credit card fraud in online …
Data mining had played an imperative role in the detection of credit card fraud in online …
Review of classification methods on unbalanced data sets
L Wang, M Han, X Li, N Zhang, H Cheng - Ieee Access, 2021 - ieeexplore.ieee.org
This paper studies the classification of unbalanced data sets. First, this kind of data sets is
briefly introduced, and then the classification methods of unbalanced data sets are analyzed …
briefly introduced, and then the classification methods of unbalanced data sets are analyzed …
An experimental study with imbalanced classification approaches for credit card fraud detection
Credit card fraud is a criminal offense. It causes severe damage to financial institutions and
individuals. Therefore, the detection and prevention of fraudulent activities are critically …
individuals. Therefore, the detection and prevention of fraudulent activities are critically …
A survey of predictive modeling on imbalanced domains
Many real-world data-mining applications involve obtaining predictive models using
datasets with strongly imbalanced distributions of the target variable. Frequently, the least …
datasets with strongly imbalanced distributions of the target variable. Frequently, the least …
Enhanced credit card fraud detection based on SVM-recursive feature elimination and hyper-parameters optimization
N Rtayli, N Enneya - Journal of Information Security and Applications, 2020 - Elsevier
With the growth of online shopping, Credit Card Fraud (CCF) comes out as a serious
menace. For this end, the automatic and real-time fraud detection field calls for several …
menace. For this end, the automatic and real-time fraud detection field calls for several …
Graph based anomaly detection and description: a survey
Detecting anomalies in data is a vital task, with numerous high-impact applications in areas
such as security, finance, health care, and law enforcement. While numerous techniques …
such as security, finance, health care, and law enforcement. While numerous techniques …