Classic Machine Learning Through the Eyes of an SRE — Part 8
The most dangerous output in my whole Week-1 study set wasn't a bad prediction. It was a beautiful tree.
Hierarchical clustering produces a dendrogram, that elegant diagram where every account, ticket, or incident nests inside ever-larger families. It looks like discovered truth. Stakeholders lean in. Someone screenshots it for the QBR deck.
Nothing else in the set looks as convincing while being as capable of being completely wrong. A bad K-Means gives you blobs that feel arbitrary, and people push back. A dendrogram built with the wrong linkage on flat data still looks like a family tree of your business.
Nobody pushes back on a tree.
