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.

Podrobná bibliografie
Hlavní autoři:	Srabon, Abir Alam, Abrar, Mahmudul Hasan, Rahman, Nimur, Ahmed, Washif Uddin, Hridy, Salamat Sajid
Další autoři:	Mostakim, Moin
Médium:	Diplomová práce
Jazyk:	English
Vydáno:	Brac University 2023
Témata:	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
On-line přístup:	http://hdl.handle.net/10361/22013

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