Overview of the proposed process with data processing, model development, model evaluation and explainability.

<p>Overview of the proposed process with data processing, model development, model evaluation and explainability.</p>

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Bibliographic Details
Main Author:	Md Amir Hamja (20495951) (author)
Other Authors:	Mahmudul Hasan (750862) (author), Md Abdur Rashid (10634653) (author), Md Tanvir Hasan Shourov (20495954) (author)
Published:	2025
Subjects:	Sociology Science Policy Biological Sciences not elsewhere classified Information Systems not elsewhere classified highest predictive accuracy explore advanced methods covering 156 countries 85 %, mse explainable ensemble learning world happiness report happiness factors vary exploring happiness factors rf ), gb combines ridge regression blending rgmll demonstrates 2 </ sup div >< p stacking ensemble techniques also important features blending rgmll >< sup ensemble ml stacking lrgr r </ linear regression important indicator combines lr also show happiness score happiness indices happiness index happiness features lstm ), lr ), dl ), ‘ perceptions variable importance unwanted situations universally recognized uncover changes trained models time monitoring term memory study utilizes social support related features random forest provides guidelines prime necessity open dataset inner peace individual variables includes data future research findings indicate dl algorithms critical indicator corruption ’.
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