Description Usage Arguments Value Functions
Run LDA as in the Blei 2003 paper
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | lda_original(docs, K, max_iter = 50, thresh = 1e-04, seed = NULL)
lda_original_par(
docs,
K,
max_iter = 50,
thresh = 1e-04,
seed = NULL,
cores = NULL
)
lda_noalpha(
docs,
K,
max_iter = 50,
thresh = 1e-04,
seed = NULL,
cores = NULL,
alpha = NULL
)
|
docs |
a list containing all the documents, with the vocabulary encoded e.g. docs[[1]] = c(1, 5, 2) would represent the word indices from a pre-defined vocabulary |
K |
the number of topics to look for |
max_iter |
the maximum number of EM iterations to run |
thresh |
threshold for L convergence, (L_i - L_i-1)/L_i < thresh |
seed |
set a seed for the random documents to initialise beta |
cores |
number of cores to run the E-step in parallel, if NULL all detected cores are used |
alpha |
if you want to set the exchangeable Dirichlet parameter for theta, if NULL a default value of 1/K is used |
A list of all parameters
lda_original_par
: Runs E-step in parallel
lda_noalpha
: Alpha is fixed
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