Performance evaluation of machine learning methods for credit card fraud detection using SMOTE and AdaBoost
The advance in technologies such as e-commerce and financial technology (FinTech)
applications have sparked an increase in the number of online card transactions that occur …
applications have sparked an increase in the number of online card transactions that occur …
[HTML][HTML] A comprehensive survey on deep learning-based LoRa radio frequency fingerprinting identification
LoRa enables long-range communication for Internet of Things (IoT) devices, especially
those with limited resources and low power requirements. Consequently, LoRa has …
those with limited resources and low power requirements. Consequently, LoRa has …
The adaboost approach tuned by firefly metaheuristics for fraud detection
The use of powerful classifiers is broad and the problem of fraud detection tends to benefit
from similar solutions as well. The problem in the digital age cannot be disregarded as the …
from similar solutions as well. The problem in the digital age cannot be disregarded as the …
Detecting frauds and payment defaults on credit card data inherited with imbalanced class distribution and overlap** class problems: A systematic review
Credit card payments are one popular e-payment option apart from cash payments. Recent
reports show that credit card fraud and payment defaults are increasing annually and are …
reports show that credit card fraud and payment defaults are increasing annually and are …
Detecting Fraudulent Transactions Using Stacked Autoencoder Kernel ELM Optimized by the Dandelion Algorithm
The risk of fraudulent activity has significantly increased with the rise in digital payments. To
resolve this issue there is a need for reliable real-time fraud detection technologies. This …
resolve this issue there is a need for reliable real-time fraud detection technologies. This …
Advancing Model Performance With ADASYN and Recurrent Feature Elimination and Cross-Validation in Machine Learning-Assisted Credit Card Fraud Detection: A …
Online card transactions have become more frequent due to the growth of e-commerce and
financial technology apps. However, this also means more opportunities for credit card …
financial technology apps. However, this also means more opportunities for credit card …
Credit card fraud detection: A hybrid of PSO and K-means clustering unsupervised approach
N Sharma, V Ranjan - … on Cloud Computing, Data Science & …, 2023 - ieeexplore.ieee.org
With the rise of the internet and online shop**, the use of credit cards for online purchases
skyrocketed and so did the incidents of online financial frauds. In the year 2018 alone, 24.26 …
skyrocketed and so did the incidents of online financial frauds. In the year 2018 alone, 24.26 …
Credit Card Fraud Detection: Addressing Imbalanced Datasets with a Multi-phase Approach
Credit card fraud detection plays a crucial role in safeguarding the financial security of
individuals and organizations. However, imbalanced datasets pose significant challenges to …
individuals and organizations. However, imbalanced datasets pose significant challenges to …
Optimizing Multilayer Perceptron with Cost-Sensitive Learning for Addressing Class Imbalance in Credit Card Fraud Detection
The increasing use of credit cards in global financial transactions offers significant
convenience for consumers and businesses. However, credit card fraud remains a major …
convenience for consumers and businesses. However, credit card fraud remains a major …
The AdaBoost approach tuned by SNS metaheuristics for fraud detection
Recent advances in online payment technologies drastically increased the number of online
credit card transactions, which had been additionally fueled by the recent COVID-19 …
credit card transactions, which had been additionally fueled by the recent COVID-19 …