mc
short answer
essay
Prompt
[CHOICE] Decision Rule — definition and the four most common.
Plain English answer (default view) — what you'd actually write on the test
The **decision rule** is the formula the computer uses to sort each pixel into a class. Four common ones: - **Parallelepiped** — pixel falls inside a box defined by class min/max. Fast but leaves gaps. - **Minimum Distance** — pixel goes to whichever class mean is closest. Fast and never leaves anything unclassified, but ignores class shape. - **Maximum Likelihood** — picks the class the pixel is *most probably* from, using class shape. Most accurate when classes are Gaussian. - **Mahalanobis** — like Min Distance, but the distance is *scaled* by class shape. The slower rules are smarter; the faster rules are dumber. Pick based on what you have time for and how Gaussian your classes look.
🔬 Technical version / model bullets (revealed on click) — one bullet per line
The mathematical test a supervised classifier uses to assign each pixel to a class. **Minimum Distance** — nearest class mean. **Mahalanobis Distance** — like Min Distance, scaled by class covariance. **Maximum Likelihood** — highest probability, assumes Gaussian classes. **Parallelepiped** — box-shaped regions by min/max per band. Fast, but has gaps + corner overlaps.
💡 Mnemonic / memory aid (shown on hover)
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