Questions tagged [dirichlet]
The Dirichlet distribution is a family of continuous multivariate probability distributions.
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Understanding the plate notation for gaussian mixture models and latent dirichlet allocation
I am having troubles understanding the plate notation being used in LDA and GMM.
In specific the class-variable deciding which parameters that generates the observation in GMM's and the topic-...
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Two sets of topics/words in Topic Modeling
In short, the question is: I have two sets of words per document. I would like to extract two sets of topics per document corresponding to sets of words.
To be more precise:
Document(d) can be ...
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What hyperparameter values does the LDA mallet model use by default? Is it true that the formula to calculate alpha = 5.0/n(topics)?
I am trying to figure out the default $\alpha$ & $\eta$ values used by mallet LDA, but there is not a lot of information on this. I did find a couple of answers, with no proper references, saying ...
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Hierarchical dirichlet process results
I am thinking about using hierarchical dirichlet process to model a patent dataset. I've seen that HDP uses a base distribution and assumes that every topic comes from that base distribution.
The ...
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Where can I learn the complete mathematics involved in LDA?
I have come across Latent Dirichlet Allocation (LDA) on multiple occasions while reading about sentiment analysis and recommender systems.
Where can I find good reading material which explains the ...
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Chinese restaurant process vs Dirichlet Process
On Wikipedia Dirichlet Process page, regarding the connection between the Chinese restaurant process and the Dirichlet process it's state the following
If one associates draws from the base ...
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Combine two sets of clusters
I have two sets of topics obtained from two different sets of news paper articles.
In other words, Cluster_1 = ${x_1, x_2, ..., x_n}$ includes the main topics of 'X' news paper set and Cluster_2 = ${...
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How do you work with Latent Dirichlet Allocation in practice
One need to provide LDA with a predefined number of latent topics. Let say I have a text corpus in which I hypothesize there are 10 major topics, all composed of 10 minor subtopics. My objective is to ...
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