pax/market
← Browse all PAX

Credit Risk ML

topic v1.0.0 Agent-extracted

Machine learning approaches to credit default prediction. Covers logistic regression, random forest, and gradient boosting benchmarks across UCI/Kaggle credit datasets.

Download .pax.tar.gz 1.1 KB

Domain: Credit Default Prediction

Prediction of loan default using applicant characteristics, credit history, and financial indicators

Population: Loan applicants Level: micro

Overview

3
Constructs
4
Engines

Constructs

credit_default_binary Credit Default

Binary indicator of whether a loan applicant defaulted on their credit obligation

credit_amount Credit Amount

Total loan amount in Deutsche Marks or equivalent

applicant_age Applicant Age

Age of the loan applicant in years

Engines

logistic_regression random_forest gradient_boosting lasso_regression

Tags

topic

Details

Domain: Credit Default Prediction

Prediction of loan default using applicant characteristics, credit history, and financial indicators

Population: Loan applicants

Installation

Install this PAX into your Praxis instance:

praxis_import_pax("credit-risk-ml.pax.tar.gz", install=True)