embed_tagspace {ruimtehol}

Build a Starspace model to be used for classification purposes

Description

Build a Starspace model to be used for classification purposes

Usage

embed_tagspace(
  x,
  y,
  model = "tagspace.bin",
  early_stopping = 0.75,
  useBytes = FALSE,
  ...
)

Arguments

x

a character vector of text where tokens are separated by spaces

y

a character vector of classes to predict or a list with the same length of x with several classes for each respective element of x

model

name of the model which will be saved, passed on to starspace

early_stopping

the percentage of the data that will be used as training data. If set to a value smaller than 1, 1-early_stopping percentage of the data which will be used as the validation set and early stopping will be executed. Defaults to 0.75.

useBytes

set to TRUE to avoid re-encoding when writing out train and/or test files. See writeLines for details

...

further arguments passed on to starspace except file, trainMode and fileFormat

Value

an object of class textspace as returned by starspace.

Examples

data(dekamer, package = "ruimtehol")
dekamer <- subset(dekamer, depotdat < as.Date("2017-02-01"))
dekamer$text <- strsplit(dekamer$question, "\\W")
dekamer$text <- lapply(dekamer$text, FUN = function(x) x[x != ""])
dekamer$text <- sapply(dekamer$text,
                       FUN = function(x) paste(x, collapse = " "))
dekamer$question_theme_main <- gsub(" ", "-", dekamer$question_theme_main)

set.seed(123456789)
model <- embed_tagspace(x = tolower(dekamer$text),
                        y = dekamer$question_theme_main,
                        early_stopping = 0.8,
                        dim = 10, minCount = 5)
plot(model)
predict(model, "de nmbs heeft het treinaanbod uitgebreid", k = 3)
predict(model, "de migranten komen naar europa, in asielcentra ...")
starspace_embedding(model, "de nmbs heeft het treinaanbod uitgebreid")
starspace_embedding(model, "__label__MIGRATIEBELEID", type = "ngram")

dekamer$question_themes <- gsub(" ", "-", dekamer$question_theme)
dekamer$question_themes <- strsplit(dekamer$question_themes, split = ",")
set.seed(123456789)
model <- embed_tagspace(x = tolower(dekamer$text),
                        y = dekamer$question_themes,
                        early_stopping = 0.8,
                        dim = 50, minCount = 2, epoch = 50)
plot(model)
predict(model, "de nmbs heeft het treinaanbod uitgebreid")
predict(model, "de migranten komen naar europa , in asielcentra ...")
embeddings_labels <- as.matrix(model, type = "labels")
emb <- starspace_embedding(model, "de nmbs heeft het treinaanbod uitgebreid")
embedding_similarity(emb, embeddings_labels, type = "cosine", top_n = 5)