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.

Dettagli Bibliografici
Autori principali:	Srabon, Abir Alam, Abrar, Mahmudul Hasan, Rahman, Nimur, Ahmed, Washif Uddin, Hridy, Salamat Sajid
Altri autori:	Mostakim, Moin
Natura:	Tesi
Lingua:	English
Pubblicazione:	Brac University 2023
Soggetti:	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
Accesso online:	http://hdl.handle.net/10361/22013

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