tnf_train: Train name finder model

In news-r/decipher: Natural Language Processing tools for R

Description

Train a name finder model.

Usage

tnf_train_(model, lang, data, feature.gen = NULL, name.types = NULL,
  sequence.codec = NULL, factory = NULL, resources = NULL,
  params = NULL, encoding = NULL, type = NULL)

tnf_train(model, lang, data, feature.gen = NULL, name.types = NULL,
  sequence.codec = NULL, factory = NULL, resources = NULL,
  params = NULL, encoding = NULL, type = NULL)

Arguments

model	Full path to output model file.
lang	Language which is being processed.
data	Data to be used, full path to file, usually .txt.
feature.gen	Path to the feature generator descriptor file.
name.types	Name types to use for training.
sequence.codec	sequence codec used to code name spans.
factory	A sub-class of TokenNameFinderFactory.
resources	The resources directory.
params	Training parameters file.
encoding	Encoding for reading and writing text, if absent the system default is used.
type	The type of the token name finder model.

Value

Full path to the model for convenience.

Examples

## Not run: 
# get working directory
# need to pass full path
wd <- getwd()

# Training to find "WEF"
data <- paste("This organisation is called the <START:wef> World Economic Forum <END>",
  "It is often referred to as <START:wef> Davos <END> or the <START:wef> WEF <END> .")

# train model
tnf_train(model = paste0(wd, "/model.bin"), lang = "en", data = data)

# Same with .txt files.
# Save the above as file
write(data, file = "input.txt")

# Trains the model and returns the full path to the model
model <- tnf_train_(model = paste0(wd, "/wef.bin"), lang = "en",
  data = paste0(wd, "/input.txt"), type = "wef")

## End(Not run)

news-r/decipher documentation built on July 19, 2019, 5:58 p.m.