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Ch. 13 – Uncertainty

Ch. 13 – Uncertainty. Supplemental slides for CSE 327 Prof. Jeff Heflin. Bayes’ Rule. formula P(C|E) = P(E|C)P(C) / P(E) example let m = meningitis, s = stiff neck P(s|m) = .8, P(m) = 0.0001, P(s) = 0.1 P(m|s) = P(s|m) P(m) / P(s) = .8(0.0001) / 0.1 = 0.0008. Full Joint Distribution.

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Ch. 13 – Uncertainty

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  1. Ch. 13 – Uncertainty Supplemental slides for CSE 327 Prof. Jeff Heflin

  2. Bayes’ Rule • formula • P(C|E) = P(E|C)P(C) / P(E) • example • let m = meningitis, s = stiff neck • P(s|m) = .8, P(m) = 0.0001, P(s) = 0.1 • P(m|s) = P(s|m) P(m) / P(s) = .8(0.0001) / 0.1 = 0.0008

  3. Full Joint Distribution • P(rainy) = 0.11 + 0.04 = 0.15 • P(sleepy) = 0.05 + 0.04 + 0.10 + 0.01 = 0.20 • P(cloudy  snow) = 0.30 + 0.10 + 0.04 + 0.01 = 0.45 • P(sleepy  sunny) = 0.05 + 0.04 + 0.10 + 0.01 + 0.35 = 0.55

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