---
title: Machine Learning vs. Logistic Regression
url: https://www.ml-quant.com/papers/repec/ids-ijmefi-v-17-y-2024-i-1-p-29-48/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:ids:ijmefi:v:17:y:2024:i:1:p:29-48
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.inderscience.com%2Flink.php%3Fid%3D137545%3Bh%3Drepec%3Aids%3Aijmefi%3Av%3A17%3Ay%3A2024%3Ai%3A1%3Ap%3A29-48
featured: 2024-04-24
citations: unknown
topic: ML & AI Methods
---


# Machine Learning vs. Logistic Regression

Machine learning models, particularly XGBoost, outperform logistic regressions in predicting credit risk in Brazilian wholesale firms, according to a study.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.inderscience.com%2Flink.php%3Fid%3D137545%3Bh%3Drepec%3Aids%3Aijmefi%3Av%3A17%3Ay%3A2024%3Ai%3A1%3Ap%3A29-48
- Identifier: RePEc:ids:ijmefi:v:17:y:2024:i:1:p:29-48
- Released: 2024-04-24
- First featured: Quant Letter No. 46 (2024-04-24): https://www.ml-quant.com/issues/2024-04-24/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: ML & AI Methods

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