What is outlier detection in data mining?

Updated May 15, 2026

Short answer

It identifies rare or abnormal data points.

Deep explanation

Outlier detection finds anomalies using statistical methods, clustering, or distance-based approaches. It is critical in fraud detection and monitoring systems.

Real-world example

Detecting fraudulent credit card transactions.

Common mistakes

  • Treating all outliers as errors.

Follow-up questions

  • What is Isolation Forest?
  • What is z-score method?

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