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Daphne Koller Bayesian Networks Semantics & Factoriza tion Probabilistic Graphical Models Representation
12

Semantics & Factorization

Dec 31, 2015

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Representation. Probabilistic Graphical Models. Bayesian Networks. Semantics & Factorization. P(G,D,I,S,L). G rade Course D ifficulty Student I ntelligence Student S AT Reference L etter. Difficulty. Intelligence. Grade. SAT. Letter. d 0. d 1. i 0. i 1. 0.6. 0.4. 0.7. - PowerPoint PPT Presentation
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Page 1: Semantics & Factorization

Daphne Koller

Bayesian Networks

Semantics & Factorization

ProbabilisticGraphicalModels

Representation

Page 2: Semantics & Factorization

Daphne Koller

• Grade• Course Difficulty• Student Intelligence • Student SAT• Reference Letter

P(G,D,I,S,L)

Page 3: Semantics & Factorization

Daphne Koller

IntelligenceDifficulty

Grade

Letter

SAT

Page 4: Semantics & Factorization

Daphne Koller

IntelligenceDifficulty

Grade

Letter

SAT

0.30.080.250.4

g2(B)

0.020.9i1,d0

0.70.05i0,d1

0.5

0.3g1(A) g3(C

)

0.2i1,d1

0.3i0,d0

l1l0

0.99

0.40.1 0.9g1

0.01g3

0.6g2

0.20.95

s0 s1

0.8i10.05i0

0.40.6

d1d0

0.30.7i1i0

Page 5: Semantics & Factorization

Daphne Koller

IntelligenceDifficulty

Grade

Letter

SAT

P(D) P(I)

P(G|I,D) P(S|I)

P(L|G)

Chain Rule for Bayesian Networks

P(D,I,G,S,L) = P(D) P(I) P(G|I,D) P(S|I) P(L|G)

Distribution defined as a product of factors!

Page 6: Semantics & Factorization

Daphne Koller

IntelligenceDifficulty

Grade

Letter

SAT

0.30.080.250.4g2

0.020.9i1,d0

0.70.05i0,d1

0.5

0.3g1 g3

0.2i1,d1

0.3i0,d0

l1l0

0.99

0.40.1 0.9g1

0.01g3

0.6g2

0.20.95

s0 s1

0.8i10.05i0

0.40.6

d1d0

0.30.7i1i0

P(d0, i1, g3, s1, l1) =

Page 7: Semantics & Factorization

Daphne Koller

Bayesian Network• A Bayesian network is:– A directed acyclic graph (DAG) G whose

nodes represent the random variables X1,…,Xn

– For each node Xi a CPD P(Xi | ParG(Xi))

• The BN represents a joint distributionvia the chain rule for Bayesian networksP(X1,…,Xn) = i P(Xi | ParG(Xi))

Page 8: Semantics & Factorization

Daphne Koller

BN Is a Legal Distribution: P ≥ 0

Page 9: Semantics & Factorization

Daphne Koller

BN Is a Legal Distribution: ∑ P = 1

∑D,I,G,S,L P(D,I,G,S,L) = ∑D,I,G,S,L P(D) P(I) P(G|I,D) P(S|I) P(L|G)

= ∑D,I,G,S P(D) P(I) P(G|I,D) P(S|I) ∑L P(L|G)

= ∑D,I,G,S P(D) P(I) P(G|I,D) P(S|I)

= ∑D,I,G P(D) P(I) P(G|I,D) ∑S P(S|I)

= ∑D,I P(D) P(I) ∑G P(G|I,D)

Page 10: Semantics & Factorization

Daphne Koller

P Factorizes over G• Let G be a graph over X1,…,Xn.

• P factorizes over G if

P(X1,…,Xn) = i P(Xi | ParG(Xi))

Page 11: Semantics & Factorization

Daphne Koller

Genetic Inheritance

Homer

Bart

Marge

Lisa Maggie

Clancy Jackie

Selma

Genotype

Phenotype

AA, AB, AO, BO, BB, OO

A, B, AB, O

Page 12: Semantics & Factorization

Daphne Koller

BNs for Genetic Inheritance

GHomer

GBart

GMarge

GLisa GMaggie

GClancy GJackie

GSelma

BClancy BJackie

BSelmaBHomer BMarge

BBart BLisa BMaggie