Description Usage Arguments Value Slots Examples
S4 class to represent a SLDAX general model that inherits from Mlr and Logistic.
Helper function (constructor) for Sldax
class
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 | ## S4 method for signature 'Sldax'
topics(x)
## S4 replacement method for signature 'Sldax'
topics(x) <- value
## S4 method for signature 'Sldax'
theta(x)
## S4 replacement method for signature 'Sldax'
theta(x) <- value
## S4 method for signature 'Sldax'
beta_(x)
## S4 replacement method for signature 'Sldax'
beta_(x) <- value
## S4 method for signature 'Sldax'
gamma_(x)
## S4 replacement method for signature 'Sldax'
gamma_(x) <- value
## S4 method for signature 'Sldax'
alpha(x)
## S4 replacement method for signature 'Sldax'
alpha(x) <- value
## S4 method for signature 'Sldax'
ntopics(x)
## S4 replacement method for signature 'Sldax'
ntopics(x) <- value
## S4 method for signature 'Sldax'
nvocab(x)
## S4 replacement method for signature 'Sldax'
nvocab(x) <- value
Sldax(nvocab, topics, theta, beta, ntopics = 2, alpha = 1, gamma = 1, ...)
|
x |
An |
value |
A value to assign to a slot for |
nvocab |
The number of terms in the corpus vocabulary. |
topics |
A D x max(N_d) x M numeric array of topic draws. 0 indicates an unused word index (i.e., the document did not have a word at that index). |
theta |
A D x K x M numeric array of topic proportions. |
beta |
A K x V x M numeric array of topic-vocabulary distributions. |
ntopics |
The number of topics for the LDA model (default: |
alpha |
A numeric prior hyperparameter for theta (default: |
gamma |
A numeric prior hyperparameter for beta (default: |
... |
additional arguments to be passed to the low level regression fitting functions (see below). |
A Sldax object.
nvocab
The number of terms in the corpus vocabulary.
ntopics
The number of topics for the LDA model.
alpha
A numeric prior hyperparameter for theta.
gamma
A numeric prior hyperparameter for beta.
topics
A D x max(N_d) x M numeric array of topic draws. 0 indicates an unused word index (i.e., the document did not have a word at that index).
theta
A D x K x M numeric array of topic proportions.
beta
A K x V x M numeric array of topic-vocabulary distributions.
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