Unveiling underlying patterns, drivers and anomalies in cryptocurrency price dynamics through feature fusion of financial indicators and sentiment fluctuations

Unveiling underlying patterns, drivers and anomalies in cryptocurrency price dynamics through feature fusion of financial indicators and sentiment fluctuations

This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science, 2024.

Détails bibliographiques
Auteur principal:	Rabbi, Md. Nafis
Autres auteurs:	Alam, Md. Golam Rabiul
Format:	Thèse
Langue:	English
Publié:	Brac University 2024
Sujets:	Logistic regression Random forest regressor Sentiment analysis Naive Bayes Gaussian Data fusion Bitcoin. Cryptocurrencies > Prices
Accès en ligne:	http://hdl.handle.net/10361/24031

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