anomaly-detector
Anomaly Detector
Overview
Detect unusual patterns, outliers, and anomalies in data using statistical methods, machine learning, and deep learning. Critical for fraud detection, security monitoring, quality control, and system health monitoring—all integrated with SpecWeave's increment workflow.
Why Anomaly Detection is Different
Challenge: Anomalies are rare (0.1% - 5% of data)
Standard classification doesn't work:
- ❌ Extreme class imbalance
- ❌ Unknown anomaly patterns
- ❌ Expensive to label anomalies
- ❌ Anomalies evolve over time
Anomaly detection approaches:
- ✅ Unsupervised (no labels needed)
- ✅ Semi-supervised (learn from normal data)
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