Apache Log Anomaly Detection: Multi-Model Analysis with Isolation Forest, One-Class SVM & More
This video presents a comprehensive analysis of anomaly detection in Apache web server logs using unsupervised machine learning models. It covers the full research pipeline — from memory optimization and feature engineering to cross-validation, model benchmarking, and performance visualization.
📌 What You’ll Learn:
Efficient parsing and preprocessing of Apache logs
Feature extraction techniques for anomaly detection
Detailed comparison of 5 unsupervised models:
Isolation Forest
One-Class SVM
Local Outlier Factor
Elliptic Envelope
SGD OneClassSVM
Model stability and performance benchmarking
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