textmining (version 0.0.1)

topic_table: Function to calculate topics and words arrays from the mallet model.

Description

Function to calculate topics and words arrays from the mallet model.

Usage

topic_table(model)

Arguments

model

tmTopicModel mallet type model.

Value

topics Array of the topics.words Array of the most important words in topic.

Examples

## Not run: 
# library(rJava)
# x <- tmCorpus(lapply(1:100, function(x) paste(sample(LETTERS, 11),
#                                               collapse = "")))
# 
# model <- train(x)
# new_x <- tmCorpus(lapply(1:100, function(x) paste(sample(LETTERS, 11),
#                                                   collapse = "")))
# 
# 
# topic_table(model)
# 
# y <- DocumentTermMatrix(x)
# rownames(y) <- meta(x, "title")
# jss_TM <-
#   list(VEM = train(y, k = k, control = list(seed = SEED)),
#        VEM_fixed = train(y, k = k,
#                          control = list(estimate.alpha = FALSE, seed = SEED)),
#        Gibbs = train(y, k = k, method = "Gibbs",
#                      control = list(seed = SEED, burnin = 1000,
#                                     thin = 100, iter = 1000)))
# pred_VEM <- predict(jss_TM$VEM, new_x)
# ## End(Not run)