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This project seeks to solve the problem of upi fraud detection by using machine learning techniques, particularly by utilizing a hidden markov model (hmm). This project focuses on developing an intelligent upi fraud detection system using data analytics and machine learning techniques to enhance transaction security. In summary, this research seeks to design a reliable and explainable machine learning model for upi fraud detection, address challenges associated with imbalanced dataset, and develop an.
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This document discusses the development of a upi fraud detection system using machine learning algorithms to address the rising cases of fraud in digital payments. Upi fraud detection using machine learning project with source code and documents. The document discusses a project focused on upi fraud detection using machine learning algorithms, specifically random forest and adaboost, to improve accuracy and efficiency in.
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The proposed system is designed to predict fraudulent transactions in the upi ecosystem using machine learning models.
The primary objective is to.
