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Machine Learning for Crypto Anomaly Detection by Minh Vũ Công is a document available to read on EtoBox.

What is Machine Learning for Crypto Anomaly Detection about?

The document discusses the use of machine learning techniques for anomaly detection in cryptocurrency transactions, emphasizing the need for effective fraud prevention due to the decentralized nature of cryptocurrencies. It compares supervised learning methods, such as Decision Trees and Neural Networks, with unsupervised techniques like Clustering and Isolation Forests, highlighting their respective advantages and challenges. The study also underscores the importance of explainable AI tools to enhance user

Author

Minh Vũ Công

Language

EN