Machine learning and Feature Selection: Applications in Business Management

Siyao Chen; Abhit Daiya; Rubhrat Deb

doi:10.70393/6a6574626d.323438

Authors

Siyao Chen University of Connecticut
Abhit Daiya University of Connecticut
Rubhrat Deb Wildlife Institute of India

DOI:

https://doi.org/10.70393/6a6574626d.323438

ARK:

https://n2t.net/ark:/40704/JETBM.v1n6a05

Disciplines:

Business

Subjects:

Business Strategy

References:

18

Keywords:

Machine Learning, Feature Selection, Business Management

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.

Author Biographies

Siyao Chen, University of Connecticut

University of Connecticut, USA.

Abhit Daiya, University of Connecticut

University of Connecticut, USA.

Rubhrat Deb, Wildlife Institute of India

Wildlife Institute of India, India.

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