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https://github.com/santiagoguty/network-traffic-anomaly-detection-using-logistic-regression
A predictive model for detecting anomalous network traffic using the UNSW-NB15 dataset created in R, leveraging logistic regression in R. Employed data cleaning, feature selection, and confusion matrix analysis to optimize model accuracy.
https://github.com/santiagoguty/network-traffic-anomaly-detection-using-logistic-regression
Last synced: about 16 hours ago
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A predictive model for detecting anomalous network traffic using the UNSW-NB15 dataset created in R, leveraging logistic regression in R. Employed data cleaning, feature selection, and confusion matrix analysis to optimize model accuracy.
- Host: GitHub
- URL: https://github.com/santiagoguty/network-traffic-anomaly-detection-using-logistic-regression
- Owner: SantiagoGuty
- Created: 2024-11-23T04:55:22.000Z (2 months ago)
- Default Branch: main
- Last Pushed: 2024-11-23T05:04:33.000Z (2 months ago)
- Last Synced: 2024-11-23T05:24:49.991Z (2 months ago)
- Language: HTML
- Size: 0 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0