keyATM {keyATM} | R Documentation |
keyATM main function
Description
Fit keyATM models.
Usage
keyATM(
docs,
model,
no_keyword_topics,
keywords = list(),
model_settings = list(),
priors = list(),
options = list(),
keep = c()
)
Arguments
docs |
texts read via keyATM_read() .
|
model |
keyATM model: base , covariates , and dynamic .
|
no_keyword_topics |
the number of regular topics.
|
keywords |
a list of keywords.
|
model_settings |
a list of model specific settings (details are in the online documentation).
|
priors |
a list of priors of parameters.
|
options |
a list of options
-
seed: A numeric value for random seed. If it is not provided, the package randomly selects a seed.
-
iterations: An integer. Number of iterations. Default is 1500 .
-
verbose: If TRUE , it prints loglikelihood and perplexity. Default is FALSE .
-
llk_per: An integer. If the value is j keyATM stores loglikelihood and perplexity every j iteration. Default value is 10 per iterations
-
use_weights: If TRUE use weight. Default is TRUE .
-
weights_type: There are four types of weights. Weights based on the information theory (information-theory ) and inverse frequency (inv-freq ) and normalized versions of them (information-theory-normalized and inv-freq-normalized ). Default is information-theory .
-
prune: If TRUE rume keywords that do not appear in the corpus. Default is TRUE .
-
store_theta: If TRUE or 1 , it stores \theta (document-topic distribution) for the iteration specified by thinning. Default is FALSE (same as 0 ).
-
store_pi: If TRUE or 1 , it stores \pi (the probability of using keyword topic word distribution) for the iteration specified by thinning. Default is FALSE (same as 0 ).
-
thinning: An integer. If the value is j keyATM stores following parameters every j iteration. The default is 5 .
-
theta: For all models. If store_theta is TRUE document-level topic assignment is stored (sufficient statistics to calculate document-topic distributions theta ).
-
alpha: For the base and dynamic models. In the base model alpha is shared across all documents whereas each state has different alpha in the dynamic model.
-
lambda: coefficients in the covariate model.
-
R: For the dynamic model. The state each document belongs to.
-
P: For the dynamic model. The state transition probability.
-
parallel_init: Parallelize processes to speed up initialization. Default is FALSE . Please plan() before use this feature.
-
resume: The resume argument is used to save and load the intermediate results of the keyATM fitting process, allowing you to resume the fitting from a previous state. The default value is NULL (do not resume).
|
keep |
a vector of the names of elements you want to keep in output.
|
Value
A keyATM_output
object containing:
- keyword_k
number of keyword topics
- no_keyword_topics
number of no-keyword topics
- V
number of terms (number of unique words)
- N
number of documents
- model
the name of the model
- theta
topic proportions for each document (document-topic distribution)
- phi
topic specific word generation probabilities (topic-word distribution)
- topic_counts
number of tokens assigned to each topic
- word_counts
number of times each word type appears
- doc_lens
length of each document in tokens
- vocab
words in the vocabulary (a vector of unique words)
- priors
priors
- options
options
- keywords_raw
specified keywords
- model_fit
perplexity and log-likelihood
- pi
estimated \pi
(the probability of using keyword topic word distribution) for the last iteration
- values_iter
values stored during iterations
- kept_values
outputs you specified to store in keep
option
- information
information about the fitting
See Also
https://keyatm.github.io/keyATM/articles/pkgdown_files/Options.html
Examples
## Not run:
library(keyATM)
library(quanteda)
data(keyATM_data_bills)
bills_keywords <- keyATM_data_bills$keywords
bills_dfm <- keyATM_data_bills$doc_dfm # quanteda dfm object
keyATM_docs <- keyATM_read(bills_dfm)
# keyATM Base
out <- keyATM(docs = keyATM_docs, model = "base",
no_keyword_topics = 5, keywords = bills_keywords)
# Visit our website for full examples: https://keyatm.github.io/keyATM/
## End(Not run)
[Package
keyATM version 0.5.2
Index]