Bayes Rule

120 views

Published on

Published in: Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
120
On SlideShare
0
From Embeds
0
Number of Embeds
28
Actions
Shares
0
Downloads
1
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Bayes Rule

  1. 1. Bayes Rule Prior (局部) C Joint (整体) Normalizer (整体) P(C, Pos) = P(C) * P(Pos | C) = 0.009 Pos P(C) = 1% P(!C) = 99% P(Pos | C) = 90% P(Pos) = P(C, Pos) + P(!C, Pos) P(!C, Pos) = P(!C) * P(Pos | !C) = 0.099 C Pos P(Neg | !C) = 90% P(Pos | !C) = 10% P( C | Pos) = P( C, Pos) / P(Pos) P(!C | Pos) = P(!C, Pos) / P(Pos) = 1 – P(C | Pos) Posterior (局 部) Kelly Chan | Nov 7 2013
  2. 2. Bayes Calculation P(A) = 0.2 P(B) = 0.8 P(R | A) = 0.1 P(R | B) = 0.4 P(A | R) = P(A, R) / P(R) P(B | R) = P(B, R) / P(R) P(!R | A) = 0.9 P(!R | B) = 0.6 P(A, R) = P(A) * P(R | A) P(B, R) = P(B) * P(R | B) 1 !R is important. Prior (局部概率) Step1. Not? Step2. Total? Multiple? Joint (局部整体) Step3. Part? Divide? Posterior (局 部) Normalizer (整体) 2 !R is hidden. P(A | R) = P(A,R) / P (R) = P(A) * P(R | A) / [P(A) * P(R | A) + P(B) * P(R | B)] 3 Row and Column could be expanded. R (?) 0.34 !R (?) 0.66 A (0.2) (0.1) 0.02 (0.9) 0.18 B (0.8) (0.4) 0.32 (0.6) 0.48 Kelly Chan | Nov 7 2013

×