Default risk prediction and feature extraction using a penalized deep neural network
From MaRDI portal
Publication:2080353
DOI10.1007/s11222-022-10140-zzbMath1496.62015OpenAlexW4296121634MaRDI QIDQ2080353
Nan Qiao, Wenli Zhang, Shuangge Ma, Yang Li, Cun-Jie Lin
Publication date: 7 October 2022
Published in: Statistics and Computing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11222-022-10140-z
Applications of statistics to economics (62P20) Computational methods for problems pertaining to statistics (62-08) Artificial neural networks and deep learning (68T07) Reliability and life testing (62N05)
Cites Work
- Unnamed Item
- On the Weibull-Gamma frailty model, its infinite moments, and its connection to generalized log-logistic, logistic, Cauchy, and extreme-value distributions
- Variable selection in the accelerated failure time model via the bridge method
- A forward and backward stagewise algorithm for nonconvex loss functions with adaptive Lasso
- Disentangling and assessing uncertainties in multiperiod corporate default risk predictions
- Machine learning: Trends, perspectives, and prospects
- The Robust Inference for the Cox Proportional Hazards Model
- Survival Analysis Methods for Personal Loan Data
- A Class of Discrete Transformation Survival Models With Application to Default Probability Prediction
- A Relabeling Approach to Handling the Class Imbalance Problem for Logistic Regression
- Definitions, methods, and applications in interpretable machine learning
- Neural network survival analysis for personal loan data
- A logistic regression model for consumer default risk
This page was built for publication: Default risk prediction and feature extraction using a penalized deep neural network