essential
likely
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Minimum Distance classifier — advantages and disadvantages?
Plain English (default view) — short, conversational, lightly seasoned with science
🔬 Scientific / formula (revealed on click) — markdown + $$…$$ ok
**✅ 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
💡 Mnemonic / memory aid (shown on hover)
Min Distance: everyone gets a class (no gaps) but weird pixels get force-fit. Ignores shape. Opposite of Parallelepiped (which leaves gaps).
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