Machine Learning for Credit Risk in the Reactive Peru Program: A Comparison of the Lasso and Ridge Regression Models

COVID-19 has caused an economic crisis in the business world, leaving limitations in the continuity of the payment chain, with companies resorting to credit access. This study aimed to determine the optimal machine learning predictive model for the credit risk of companies under the Reactiva Peru Pr...

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Autores principales: Luis Alberto Geraldo Campos, Juan J. Soria, Tamara Pando-Ezcurra
Formato: Artículo
Lenguaje:inglés
Publicado: 2022
Materias:
Lasso (programming language)
Credit risk
Elastic net regularization
Regression analysis
Computer science
Machine learning
Multivariate adaptive regression splines
Regression
Logistic regression
Population
Artificial intelligence
Econometrics
Statistics
Actuarial science
Nonparametric regression
Mathematics
Economics
Feature selection
Medicine
Environmental health
World Wide Web
Social Sciences Economics, Econometrics and Finance Economics and Econometrics Business, Innovation, and Economy
Social Sciences Business, Management and Accounting Accounting Business, Education, Mathematics Research
Social Sciences Business, Management and Accounting Accounting Financial Distress and Bankruptcy Prediction
Acceso en línea:Ver en el sistema de origen
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