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.

Bibliographische Detailangaben
Hauptverfasser:	Srabon, Abir Alam, Abrar, Mahmudul Hasan, Rahman, Nimur, Ahmed, Washif Uddin, Hridy, Salamat Sajid
Weitere Verfasser:	Mostakim, Moin
Format:	Abschlussarbeit
Sprache:	English
Veröffentlicht:	Brac University 2023
Schlagworte:	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
Online Zugang:	http://hdl.handle.net/10361/22013

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