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**Maximum Likelihood (2) — when it applies.** - The most commonly used decision rule in supervised classification. - **Assumptions:** - Prior probabilities are **equal for all classes** (drop this → Bayesian rule, slide 15). - Each input band has a **normal distribution** inside each class. - Works well when classes are well-sampled and spectrally distinct; struggles on rare classes or non-Gaussian distributions.

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