Structure

MLSupportVectorClassifier.ModelParameters

Parameters that affect the process of training a model.

Declaration

struct MLSupportVectorClassifier.ModelParameters

Topics

Creating Parameters

init(validationData: MLDataTable?, maxIterations: Int, penalty: Double, convergenceThreshold: Double, featureRescaling: Bool)

Creates a new set of parameters.

Deprecated

Accessing Parameters

var convergenceThreshold: Double
var featureRescaling: Bool
var maxIterations: Int
var penalty: Double
var validationData: MLDataTable?Deprecated

Describing Parameters

var description: String

A text representation of the model parameters for a support vector classifier.

var debugDescription: String

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

var playgroundDescription: Any

A description of the model parameters for a support vector classifier shown in a playground.

Initializers

init(validation: MLSupportVectorClassifier.ModelParameters.ValidationData, maxIterations: Int, penalty: Double, convergenceThreshold: Double, featureRescaling: Bool)

Instance Properties

var validation: MLSupportVectorClassifier.ModelParameters.ValidationData

Enumerations

enum MLSupportVectorClassifier.ModelParameters.ValidationData

Relationships

Conforms To

See Also

Creating and Training a Support Vector Classifier

init(trainingData: MLDataTable, targetColumn: String, featureColumns: [String]?, parameters: MLSupportVectorClassifier.ModelParameters)

Creates a Support Vector Classifier from the feature columns in the training data to predict the categories in the target column.

let modelParameters: MLSupportVectorClassifier.ModelParameters

The underlying parameters used when training the model.

var targetColumn: String

The name of the column you selected at initialization to define which categories the classifier predicts.

var featureColumns: [String]

The names of the columns you selected at initialization to train the classifier.