devtools::load_all()
topics <- c(2,5,10,25,50,seq(100,500,100))
dp_models <- system.file("model", package="maxmodelr")
# //////////////// #
# /// ALL_LANG /// #
# //////////////// #
system.time({
cat("start preparing eng title corpus...\n")
data(titles_eng, package="maxplanckr")
dtcorp <- topmodelr::prepare_dt_corpus(titles_eng)
dtcorp <- topmodelr::filter_dt_corpus(dtcorp,1,1)
cat("done preparing eng title corpus...\n")
vocab <- dtcorp$ncol
docs <- dtcorp$nrow
cat(paste("corpus has", docs, "documents and", vocab, "terms...\n"))
cat("start modeling eng titles...\n")
topmodelr::fit_and_save_models(
dtcorp,
topics=topics,
fileid="all_lang",
model_dir=dp_models
)
cat("done modeling eng titles...\n")
})
# //////////////// #
# /// MPI_LANG /// #
# //////////////// #
system.time({
cat("start preparing mpi title corpus...\n")
data(titles_mpi, package="maxplanckr")
dtcorp <- topmodelr::prepare_dt_corpus(titles_mpi)
dtcorp <- topmodelr::filter_dt_corpus(dtcorp,1,1)
cat("done preparing mpi title corpus...\n")
vocab <- dtcorp$ncol
docs <- dtcorp$nrow
cat(paste("corpus has", docs, "documents and", vocab, "terms...\n"))
cat("start modeling mpi titles...\n")
topmodelr::fit_and_save_models(
dtcorp,
topics=topics,
fileid="mpi_lang",
model_dir=dp_models
)
cat("done modeling mpi titles!\n\n")
})
# ///////////////// #
# /// PERS_LANG /// #
# ///////////////// #
system.time({
cat("start preparing pers title corpus...\n")
data(titles_pers, package="maxplanckr")
dtcorp <- topmodelr::prepare_dt_corpus(titles_pers)
dtcorp <- topmodelr::filter_dt_corpus(dtcorp,1,1)
cat("done preparing pers title corpus...\n")
vocab <- dtcorp$ncol
docs <- dtcorp$nrow
cat(paste("corpus has", docs, "documents and", vocab, "terms...\n"))
cat("start modeling pers titles...\n")
topmodelr::fit_and_save_models(
dtcorp,
topics=topics,
fileid="pers_lang",
model_dir=dp_models
)
cat("done modeling pers titles!\n\n")
})
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