Purpose-Built Anomaly Detectors

Isolation Forest, One-Class SVM and Local Outlier Factor, three algorithms built specifically to answer how anomalous a single point is, each with a different notion of unusual, and the outlier-versus-novelty mode distinction a production IDS actually needs.

~5 min total·4 quadrants of structured content

By the end of this topic, you will

Name three purpose-built anomaly detectors and how each one decides a point is anomalous
Run Isolation Forest, One-Class SVM and Local Outlier Factor in scikit-learn
Explain the difference between outlier detection mode and novelty mode and which one a production IDS needs

Quadrant 1 · e-Tutorial

Video lectures and walkthroughs

Video content coming soon.

Quadrant 2 · e-Content

Articles and case studies

Purpose-Built Anomaly Detectors

Clustering finds structure as a side effect of grouping. These three algorithms are built specifically to answer one question for one point at a time: how anomalous is this?

Quadrant 3 · Web Resources