Скачать или смотреть WSN attack detection using Random forest & XGB machine learning | Final year ML projects for BE

In this video, we demonstrate the output results of a machine learning-based attack detection system for Wireless Sensor Networks (WSNs) using Random Forest and XGB algorithms.

This video provides:
A brief overview of the project
Live code execution (partial view)
Visualization of the detection results
Comparison between Random forest and XGB performance

📊 Performance Metrics Discussed:
Accuracy
Precision
Recall
F1-score
Kappa
Confusion matrix
ROC curve
AUC Score

Tools & Technologies Used:
Python
scikit-learn
Matplotlib / Seaborn

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