MIT15_097S12_lec15

# Even using conjugate priors in general it will not be

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Unformatted text preview: . 21 In addition to the graph structure, we use plates to denote repeated, inde­ pendent draws from the same distribution. The plates are like the ‘for’ loops in the pseudocode of how the data is generated in the text description above. Coin Flip Example Part 7. Even simple models like the coin ﬂip model can be represented graphically. The coin ﬂip model is: 5.3 Inference in hierarchical models Hierarchical models are useful because they allow us to model interactions between the observed variables (in this case the words in each document) through the use of latent (or hidden) variables. What are the latent variables for LDA? Despite introducing a larger number of latent variables than we have observed variables, because of their additional structure hierarchical models are gen­ erally not as prone to overﬁtting as you might expect. We are interested in infering the posterior distribution for the latent vari­ ables. Let Z = {zi,j }i=1,...,m,j =1,...,ni , θ = {θi }i=1,...,m , φ = {φk }k=1,...,K , and W = {wi,j }i=1,...,m,j =1,...,ni . Then, by Baye...
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## This note was uploaded on 03/24/2014 for the course MIT 15.097 taught by Professor Cynthiarudin during the Spring '12 term at MIT.

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