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.

Bibliografische gegevens
Hoofdauteur:	Rabbi, Md. Nafis
Andere auteurs:	Alam, Md. Golam Rabiul
Formaat:	Thesis
Taal:	English
Gepubliceerd in:	Brac University 2024
Onderwerpen:	Logistic regression Random forest regressor Sentiment analysis Naive Bayes Gaussian Data fusion Bitcoin. Cryptocurrencies > Prices
Online toegang:	http://hdl.handle.net/10361/24031

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