semasuka/Credit-card-approval-prediction-classification
Credit risk analysis for credit card applicants
Implements binary classification using gradient boosting to predict approval likelihood without hard credit inquiries, achieving 90% recall on applicant data. Leverages exploratory and multivariate correlation analysis to identify income and relationship status as top predictive features. Deploys via Streamlit frontend with models hosted on AWS S3 for production inference.
301 stars. No commits in the last 6 months.
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License
MIT
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Last pushed
Oct 19, 2024
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