Comparative Analysis of Methods for Detecting Fraudulent Transactions

This article is focused on the comparative analysis of machine learning models used to identify fraudulent transactions. During the research, models of three different algorithms were considered, and their optimization for the task was performed. The accuracy of the models was compared, the advantages and disadvantages of each model were identified, recommendations for their use were given, and conclusions were drawn. The experiment was conducted to evaluate the effectiveness of various machine learning models in transaction classification problems.