What is 'Isolation Forest'?

Approach: Describe an anomaly detection algorithm that 'isolates' observations by randomly splitting features.

An anomaly detection algorithm that works by isolating observations by randomly selecting a feature and then randomly selecting a split value. Anomalies are easier to isolate and thus have shorter path lengths in the trees.

Follow-up: Why is it efficient for high-dimensional data?

Key concepts: outliers, path length, ensemble.