EE7750
MACHINE RECOGNITION OF PATTERNS
Lecture 3: Bayesian Decision Theory

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Bayesian Decision Theory
Return to the fish example. There are two categories.
Denote these categories as w
1
for sea bass and w
2
for
salmon.
Assume that there is some
prior probability
(or simply
prior
) P(w
1
) that the next fish is sea bass, and some
prior probability that P(w
2
) that it is salmon.
Suppose that we make a decision without making a
measurement. The logical decision rule is
Decide w
1
if P(w
1
) > P(w
2
); otherwise decide w
2