Improving Machine Learning Performance in Credit Scoring by Data Analysis and Data Pre-Processing

Bogdan Ichim, Bogdan Ichim, Bilal Issa

2025

Abstract

In this paper we showcase several data analysis and data pre-processing techniques which, when applied to the dataset Give Me Some Credit, lead to improvements in the performance of several machine learning algorithms in classifying defaulters and non-defaulters in comparison with other existing solutions from the literature. Our study underscores the importance of these techniques in data science in general, and in enhancing the machine learning outcomes in particular.

Paper Citation

in Harvard Style

Ichim B. and Issa B. (2025). Improving Machine Learning Performance in Credit Scoring by Data Analysis and Data Pre-Processing. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 249-255. DOI: 10.5220/0013118500003890

in Bibtex Style

@conference{icaart25,
author={Bogdan Ichim and Bilal Issa},
title={Improving Machine Learning Performance in Credit Scoring by Data Analysis and Data Pre-Processing},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2025},
pages={249-255},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013118500003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Improving Machine Learning Performance in Credit Scoring by Data Analysis and Data Pre-Processing
SN - 978-989-758-737-5
AU - Ichim B.
AU - Issa B.
PY - 2025
SP - 249
EP - 255
DO - 10.5220/0013118500003890
PB - SciTePress