ML Anomaly Detection Training: Start With the Base Rate
This story is from 2026-09-09. It is preserved in the archive; the latest stories are on the live feed.
Fitting an isolation forest takes four lines of Python. Evaluating one honestly takes labeled attack data, a defensible unit of analysis, and arithmetic that most training on ML-based anomaly detection never gets around to. That imbalance is the problem. Model fitting gets the lab time because it d…
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- 2026-09-09 14:21 · DEV Community — Machine Learning
ML Anomaly Detection Training: Start With the Base Rate