Abstract

In recent years, we have a higher demand for machine learning models in the field of economics and business managment. We have a higher demand for quality of the features used for training. In this process, feature selection plays a key role in identifying the most meaningful features from a dataset while we perfrom various business tasks. Feature selection is not just a technical exercise; it also has profound implications for the transparency and explainability of machine learning models. This study aims to be a valuable resource for both academic and industry experts, offering insights that connect theoretical knowledge with practical implementation. And this paper also highlights the potential applications and significance of feature selection across industries like business, finance, and other real-world scenarios. And it aims to explore deep in the feature selection, showing that its impact on model performance and its role in various domains.

Keywords

Machine LearningFeature SelectionBusiness Management

Publication

Accepted Unknow ; Published 2024 December 16

Journal of Economic Theory and Business Management, 2024, 1(6), 3006-4953

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Metadata

DOI

10.70393/6a6574626d.323438

ARK

ark:/40704/JETBM.v1n6a05

Pages

33–38

References

18

Disciplines

Business

Subjects

Business Strategy

Cite This Article

Acknowledgments

The authors thank the editor and anonymous reviewers for their helpful comments and valuable suggestions.

Funding

Not applicable.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Informed Consent Statement

Not applicable.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Author Contributions

Not applicable.

References

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Copyright © 2024 The Author(s). Published by Southern United Academy of Sciences.
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