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.

Bibliografiska uppgifter
Huvudupphovsmän: Srabon, Abir Alam, Abrar, Mahmudul Hasan, Rahman, Nimur, Ahmed, Washif Uddin, Hridy, Salamat Sajid
Övriga upphovsmän: Mostakim, Moin
Materialtyp: Lärdomsprov
Språk:English
Publicerad: Brac University 2023
Ämnen:
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
Länkar:http://hdl.handle.net/10361/22013

Internet

http://hdl.handle.net/10361/22013

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