Initializer

init(trainingData:parameters:)

Creates a word tagger from a training set in an array of tokens and their labels.

Declaration

init(trainingData: [(tokens: [MLWordTagger.Token], labels: [String])], parameters: MLWordTagger.ModelParameters = ModelParameters(validationData: [])) throws

Parameters

trainingData

The array of tuples containing the tokens and their labels.

parameters

The model parameters to use when creating the word tagger.

Discussion

You use this initializer to create a word tagger when your training data are in arrays in memory. For example, start with an array of tokens and an array of labels, one for each token.

let tokenArray = [
  "the",
  "quick",
  "brown",
  "fox",
  "jumped",
  "over",
  "the",
  "lazy",
  "dog"]

let labelArray = [
  "article",
  "adjective",
  "adjective",
  "noun",
  "verb",
  "preposition",
  "article",
  "adjective",
  "noun"
]

Then create the word tagger by putting the arrays into a tuple.

let tupleArray = [(tokenArray, labelArray)]
let wordTagger = try MLWordTagger(trainingData: tupleArray)

See Also

Creating and Training a Word Tagger

typealias MLWordTagger.Token

The token type of a word tagger, which is String.

struct MLWordTagger.ModelParameters

Parameters that affect the process of training a model.

let modelParameters: MLWordTagger.ModelParameters

The configuration parameters that the word tagger used for training during initialization.