Minimum Distance classifier — advantages and disadvantages?
likely classification✅ Advantages - ⚡ No unclassified pixels (every pixel has some nearest mean) - 🚀 Very fast decision rule
❌ Disadvantages - 🎯 Force-fits outlier pixels that should be flagged unclassified - 📐 Ignores class variability — treats tight clusters and loose clusters equally
Min Distance: everyone gets a class (no gaps) but weird pixels get force-fit. Ignores shape. Opposite of Parallelepiped (which leaves gaps).