Enron investigation using logistic regression with LBFGS solver

Abstract

This research paper explores the application of machine learning techniques in detecting financial fraud using the Enron scandal as a case study. The Enron scandal is one of the biggest financial scandals in history, involving fraudulent accounting practices that allowed Enron to inflate its earnings and deceive investors and regulators. The paper also discusses the development of a web application to visualize the results of the analysis and provide insights to users.