Robust Cross-Validation of Predictive Models Used in Credit Default Risk
Model validation is a challenging Machine Learning task, usually more difficult for consumer credit default models because of the availability of small datasets, the modeling of low-frequency events (imbalanced data), and the bias in the explanatory variables induced by the train/test sets split of...
Saved in:
| Main Authors: | Jose Vicente Alonso, Lorenzo Escot |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/10/5495 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
CREDIT DEFAULT SWAPS IN THE MECHANISM OF REDISTRIBUTION OF CREDIT RISK
by: O. Solodka
Published: (2015-03-01) -
PENYELUNDUPAN HUKUM OLEH BANK MELALUI KLAUSUL CROSS COLLATERAL DAN CROSS DEFAULT TERHADAP PERJANJIAN KREDIT
by: Aida Ardini, et al.
Published: (2023-05-01) -
Predicting mortgage credit defaults in morocco using machine learning approaches
by: Amine Hade, et al.
Published: (2025-06-01) -
1) MULTIDIMENSIONAL SCALING FOR CREDIT DEFAULT SWAP (CDS): EVIDENCE FROM OECD COUNTRIES
by: Ayhan KAPUSUZOGLU, et al.
Published: (2018-12-01) -
Credit card default prediction using ML and DL techniques
by: Fazal Wahab, et al.
Published: (2024-01-01)