97% Accurate and Still Missing Spam

Two spam filters scored over 97% accuracy. One missed 21% of spam. Why accuracy fails on imbalanced data, and what recall and F1 reveal instead.

Linear Algebra Behind for Cybersecurity ML Models

Naive Bayes assumes every feature is independent. For spam detection, that’s provably false — words in a sentence are obviously correlated. The model works well anyway. Figuring out why a wrong assumption still produces a right answer taught me more than a correct model would have. It’s also the thing that shifted how I read…