A modular and interpretable framework for tabular data analysis using LLaMA 7B: Enhancing preprocessing, modeling, and explainability with local language models

Open Access

Peer-reviewed

Research Article

About the Authors

Shahab Ahmad Al Maaytah

Contributed equally to this work with: Shahab Ahmad Al Maaytah, Ayman Qahmash

Roles Conceptualization, Data curation, Formal analysis, Supervision

Affiliation Department of Languages and Humanities, Applied College, King Faisal University, Al-Ahsa, The Eastern Province, Saudi Arabia

Ayman Qahmash

Contributed equally to this work with: Shahab Ahmad Al Maaytah, Ayman Qahmash

Roles Data curation, Formal analysis, Funding acquisition, Writing – original draft, Writing – review & editing

Affiliation Informatics and Computer Systems Department, King Khalid University, Abha, Saudi Arabia

The authors have declared that no competing interests exist.

Preprocessing
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Computational pipelines
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Language
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Machine learning
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Metadata
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Data visualization
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Forecasting
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Alcoholism
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