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Collapsed Gibbs Sampling for LDA #113

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This is a work in progress implementation of the collapsed Gibbs sampler for the LDA model using the GraphX abstraction primitives. While this is based on the (non-ergodic) bulk synchronous Gibbs sampler, we do exploit local parameter sharing and if document vertex partitioning is used we recover the Newman et al. style sampler.

Remaining tasks:

  • Unite tests
  • Raw document processing
  • Likelihood calculation (requires log gamma transcendental functions)

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All automated tests passed.
Refer to this link for build results: https://amplab.cs.berkeley.edu/jenkins/job/GraphXPullRequestBuilder/5934/

for (i <- 0 until nIter) {
// Resample all the tokens
graph = graph.mapTriplets {
triplet => {
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Can you make this a separate named function?

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All automated tests passed.
Refer to this link for build results: https://amplab.cs.berkeley.edu/jenkins/job/GraphXPullRequestBuilder/9536/

@AmplabJenkins
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All automated tests passed.
Refer to this link for build results: https://amplab.cs.berkeley.edu/jenkins/job/GraphXPullRequestBuilder/9695/

@AmplabJenkins
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All automated tests passed.
Refer to this link for build results: https://amplab.cs.berkeley.edu/jenkins/job/GraphXPullRequestBuilder/10213/

@AmplabJenkins
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All automated tests passed.
Refer to this link for build results: https://amplab.cs.berkeley.edu/jenkins/job/GraphXPullRequestBuilder/10215/

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4 participants