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**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).

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