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Multivariate Outliers: Standardised Distance (Mahalanobis-Lite)

Lesson 6 of 815 minLab

This lesson is part of the course

In this lesson

You standardise three transaction features, combine them into one distance score and find the payment that looks normal on every single feature but odd as a whole.

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Lessons in this course

  1. Z-Score Flags: How Far from Normal Is a Transaction?Lab12 min Locked
  2. Robust Z-Scores with the Median & MADLab12 min Locked
  3. IQR Fences: Box-Plot Outliers in Server LatencyLab12 min Locked
  4. Rolling Mean ± k·σ Bands for a Live Metric (with a Chart)Lab15 min Locked
  5. Seasonal Baselines: Same Hour, Last WeeksLab14 min Locked
  6. Multivariate Outliers: Standardised Distance (Mahalanobis-Lite)Lab15 min Locked
  7. Labelled Anomalies: Precision & Recall at Each Threshold (with a Chart)Lab15 min Locked
  8. Alert Fatigue & Cost: Choosing the ThresholdLab14 min Locked