https://github.com/alessandromonolo/fraud-detection-binary-classification-model
This project builds a machine learning model to classify fraudulent clients using a banking dataset. Data preprocessing, statistical analysis, and feature selection were performed before training KNN and Random Forest Classifier. Model performance was evaluated using accuracy, precision, recall, and F1-score.
https://github.com/alessandromonolo/fraud-detection-binary-classification-model
classification-model fraud-detection knn-classification machine-learning pandas python random-forest scikit-learn statistical-analysis
Last synced: about 2 months ago
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This project builds a machine learning model to classify fraudulent clients using a banking dataset. Data preprocessing, statistical analysis, and feature selection were performed before training KNN and Random Forest Classifier. Model performance was evaluated using accuracy, precision, recall, and F1-score.
- Host: GitHub
- URL: https://github.com/alessandromonolo/fraud-detection-binary-classification-model
- Owner: alessandromonolo
- Created: 2025-02-06T15:49:11.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-06T16:09:40.000Z (over 1 year ago)
- Last Synced: 2025-02-06T17:25:20.488Z (over 1 year ago)
- Topics: classification-model, fraud-detection, knn-classification, machine-learning, pandas, python, random-forest, scikit-learn, statistical-analysis
- Language: Jupyter Notebook
- Homepage:
- Size: 1.21 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files: