View source: R/r-all-the-things.R
embed_tagspace | R Documentation |
Build a Starspace model to be used for classification purposes
embed_tagspace(
x,
y,
model = "tagspace.bin",
early_stopping = 0.75,
useBytes = FALSE,
...
)
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 |
model |
name of the model which will be saved, passed on to |
early_stopping |
the percentage of the data that will be used as training data. If set to a value smaller than 1, 1- |
useBytes |
set to TRUE to avoid re-encoding when writing out train and/or test files. See |
... |
further arguments passed on to |
an object of class textspace
as returned by starspace
.
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)
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