Parameters that affect the process of training a model.


struct MLWordTagger.ModelParameters


Creating Parameters

init(validationData: [(tokens: [MLWordTagger.Token], labels: [String])], algorithm: MLWordTagger.ModelAlgorithmType, language: NLLanguage?)

Creates a new set of word tagger parameters with validation data represented by a dictionary.

enum MLWordTagger.ModelAlgorithmType

The type of algorithm used by a word tagger.

Accessing Parameters

var algorithm: MLWordTagger.ModelAlgorithmType

The word tagger’s algorithm setting.

var language: NLLanguage?

The word tagger’s language setting.

var validationData: MLDataTable?

The word tagger’s validation data set represented by a data table.

var tokenColumnValidationData: String?

The name of the column containing the tokens in the validataion data table.

var labelColumnValidationData: String?

The name of the column containing the token labels in the validataion data table.


Describing Parameters

var description: String

A text representation of the model parameters.

var debugDescription: String

A text representation of the model parameters that’s suitable for output during debugging.

var playgroundDescription: Any

A description of the model parameters shown in a playground.

See Also

Creating and Training a Word Tagger

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

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

typealias MLWordTagger.Token

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

let modelParameters: MLWordTagger.ModelParameters

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

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