Minimum Distance (2) — advantages and disadvantages.

Advantages: - No unclassified pixels (every pixel has a nearest mean). - Fast decision rule.

Disadvantages: - Pixels that should be unclassified — because they’re not close to any training class — will still be assigned somewhere (a “force-fit”). - Does not consider class variability (two classes with very different spreads are treated equally).