Machine learning and company failure prediction: Evidence from South Africa
Orientation: Machine learning has advanced substantially over the past two decades and exhibits the potential to overcome the limitations of traditional statistical methods for predicting company failure. While extensive research has been conducted globally to predict company failure using machine l...
Saved in:
| Main Authors: | Nicolene Wesson, Dewald Mienie, Anthea Myatt |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
AOSIS
2025-03-01
|
| Series: | Acta Commercii |
| Subjects: | |
| Online Access: | https://actacommercii.co.za/index.php/acta/article/view/1365 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Factors influencing smallholder farmers’ participation in collective marketing: micro-level evidence from Ehlanzeni, South Africa
by: Nkhubedu Adelaide Magakwe, et al.
Published: (2025-07-01) -
Bankruptcy Prediction Models for Construction Companies in the Russian Federation
by: A. V. Voiko
Published: (2019-10-01) -
How Hope Defi(n)es South Africa: Reimagining Hope in Johannesburg’s Slovo Park Beyond State Failures
by: Eileen Jahn
Published: (2025-03-01) -
Factors associated with failed spinal anaesthesia for Caesarean sections in Mthatha general hospital, Eastern Cape, South Africa
by: Adeyinka Abiodun Alabi, et al.
Published: (2017-08-01) -
Machine learning‐based model for worsening heart failure risk in Chinese chronic heart failure patients
by: Ziyi Sun, et al.
Published: (2025-02-01)