Comparative analysis of machine learning models for stock price analysis across different dataset sizes

Comparative analysis of machine learning models for stock price analysis across different dataset sizes

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.

Opis bibliograficzny
Główni autorzy:	Srabon, Abir Alam, Abrar, Mahmudul Hasan, Rahman, Nimur, Ahmed, Washif Uddin, Hridy, Salamat Sajid
Kolejni autorzy:	Mostakim, Moin
Format:	Praca dyplomowa
Język:	English
Wydane:	Brac University 2023
Hasła przedmiotowe:	Stock price analysis Explainable AI Q-learning Bi-LSTM Restricted boltzmann machine LSTM Deep belief network Dataset size Performance evaluation Interpretable models Predictive accuracy Machine learning Artificial intelligence
Dostęp online:	http://hdl.handle.net/10361/22013

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