juniorAnomaly Detection
How do you handle missing values before anomaly detection?
Updated May 5, 2026
Short answer
Through imputation (mean, median) or dropping incomplete rows[cite: 1].
Deep explanation
In anomaly detection, a 'missing' value can itself be an anomaly (e.g., a sensor that stopped reporting because of a fault)[cite: 1].
Real-world example
Filling in missing temperature data using the average of the last hour[cite: 1].
Common mistakes
- Imputing values when the 'missingness' was the actual signal[cite: 1].
Follow-up questions
- What is MICE?