https://github.com/lukemercouris/loan_prediction
Loan Approval Prediction: Built binary classification model to predict loan approvals using financial and demographic data. Applied preprocessing and StandardScaler normalization. Used Gaussian Naive Bayes model achieving 92% recall for approvals, 74% accuracy, and 82% F1-score. Deployed via Flask web application.
https://github.com/lukemercouris/loan_prediction
machine-learning matplotlib pipelines python regression-algorithms regression-model seaborn sklearn streamlit
Last synced: 3 months ago
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Loan Approval Prediction: Built binary classification model to predict loan approvals using financial and demographic data. Applied preprocessing and StandardScaler normalization. Used Gaussian Naive Bayes model achieving 92% recall for approvals, 74% accuracy, and 82% F1-score. Deployed via Flask web application.
- Host: GitHub
- URL: https://github.com/lukemercouris/loan_prediction
- Owner: LukeMercouris
- Created: 2024-11-17T17:52:14.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2024-12-31T14:28:38.000Z (5 months ago)
- Last Synced: 2024-12-31T15:25:51.902Z (5 months ago)
- Topics: machine-learning, matplotlib, pipelines, python, regression-algorithms, regression-model, seaborn, sklearn, streamlit
- Language: Jupyter Notebook
- Homepage: https://loanprediction-a4amhmqrmggnrjwec89ajx.streamlit.app/
- Size: 950 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
Loan Approval Prediction: Binary classification task to predict loan approvals using a dataset of financial and demographic features. Conducted data preprocessing, feature engineering, and normalization with StandardScaler. Performed exploratory data analysis and tested models, selecting Gaussian Naive Bayes for its efficiency and high recall (92%) for approvals. Achieved 74% accuracy and 82% F1-score for the positive class. Deployed the model via Flask for web application integration.