Developing and comparing machine learning approaches for predicting insurance penetration rates based on each country
Seyed Farshid Ghorashi, Maziyar Bahri, Atousa Goodarzi
Year of publication: |
2024
|
---|---|
Authors: | Ghorashi, Farshid ; Bahri, Maziyar ; Goodarzi, Atousa |
Subject: | Decision tree | Insurance penetration rate | Machine learning | OECD countries | Random forest | XGBoost | Künstliche Intelligenz | Artificial intelligence | OECD-Staaten | Prognoseverfahren | Forecasting model | Versicherung | Insurance | Entscheidungsbaum |
Saved in:
Online Resource
Saved in favorites
Similar items by subject
-
Agrawal, Anshul, (2023)
-
Forecasting natural rubber prices using commodity market indicators : a machine learning approach
Nyondo, Precious, (2024)
-
A novel model structured on predictive churn methods in a banking organization
Silveira, Leonardo José, (2021)
- More ...