This project demonstrates how to build a fraud detection system using machine learning with the Logistic Regression algorithm. It uses the popular credit card fraud dataset and handles class imbalance ...

Abstract: Credit card fraud ... fraud detection, i.e., unbalanced data, excessive invisible features, and the choice of suitable threshold to make the models more reasonable. To overcome the above ...

This project implements a Fraud Detection model using Logistic Regression. The objective is to predict fraudulent transactions for a financial company and develop actionable insights from the model's ...

Logistic regression is a powerful statistical method that ... combination of the explanatory variables being transformed into a probability using the logistic (or sigmoid) function. The term logit ...

Logistic Regression, Deep learning. The winding path of this research into fraud detection using traditional machine learning (ML) led us through landscapes of both impressive strides and ...

This article explains how to create a logistic regression binary classification model using the PyTorch code library with ... The equation for p is called the logistic sigmoid function. When computing ...

Our results show that the logistic regression model can achieve an accuracy of 94% in detecting fraudulent transactions. Additionally, we perform feature importance analysis to identify the most ...