Booster Class Reference


                    
                    
                    booster

Pointer to underlying BoosterHandle.

Declaration

Swift

public var booster: BoosterHandle?


                    
                    
                    systemLibraryVersion

Version of underlying XGBoost system library.

Declaration

Swift

public static var systemLibraryVersion: (major: Int, minor: Int, patch: Int)


                    
                    
                    registerLogCallback(_:)

Register callback function for LOG(INFO) messages.

Declaration

Swift

public static func registerLogCallback(
    _ call: (@convention(c) (UnsafePointer<Int8>?) -> Void)?
) throws

Parameters


                                call

Function to be called with C-String as parameter. Use String(cString: $0!) co convert it into Swift string.


                    
                    
                    init(booster:)

Initialize Booster with an existing BoosterHandle pointer.

Declaration

Swift

public init(
    booster: BoosterHandle?
)

Parameters


                                booster

BoosterHandle pointer.


                    
                    
                    init(buffer:)

Initialize Booster from buffer.

Declaration

Swift

public convenience init(
    buffer: BufferModel
) throws

Parameters


                                buffer

Model serialized as buffer.


                    
                    
                    init(with:from:config:parameters:validateParameters:)

Initialize new Booster.

Declaration

Swift

public convenience init(
    with data: [Data] = [],
    from path: String? = nil,
    config: String? = nil,
    parameters: [Parameter] = [],
    validateParameters: Bool = true
) throws

Parameters

`with`	Data that will be cached.
`from`	Loads model from path.
`config`	Loads model from config.
`parameters`	Array of parameters to be set.
`validateParameters`	If true, parameters will be valided. This basically adds parameter validate_parameters=1.


                    
                    
                    reset()

Serializes and unserializes booster to reset state and free training memory.

Declaration

Swift

public func reset() throws


                    
                    
                    config()

Declaration

Swift

public func config() throws -> String

Return Value

Booster’s internal configuration in a JSON string.


                    
                    
                    attributes()

Declaration

Swift

public func attributes() throws -> [String : String]

Return Value

Attributes stored in the Booster as a dictionary.


                    
                    
                    predict(from:outputMargin:treeLimit:predictionLeaf:predictionContributions:approximateContributions:predictionInteractions:training:validateFeatures:)

Predict from data.

Declaration

Swift

public func predict(
    from data: DMatrix,
    outputMargin: Bool = false,
    treeLimit: UInt32 = 0,
    predictionLeaf: Bool = false,
    predictionContributions: Bool = false,
    approximateContributions: Bool = false,
    predictionInteractions: Bool = false,
    training: Bool = false,
    validateFeatures: Bool = true
) throws -> ArrayWithShape<Float>

Parameters

`from`	Data to predict from.
`outputMargin`	Whether to output the raw untransformed margin value.
`treeLimit`	Limit number of trees in the prediction. Zero means use all trees.
`predictionLeaf`	Each record indicating the predicted leaf index of each sample in each tree.
`predictionContributions`	Each record indicating the feature contributions (SHAP values) for that prediction.
`approximateContributions`	Approximate the contributions of each feature.
`predictionInteractions`	Indicate the SHAP interaction values for each pair of features.
`training`	Whether the prediction will be used for traning.
`validateFeatures`	Validate booster and data features.


                    
                    
                    predict(features:outputMargin:treeLimit:predictionLeaf:predictionContributions:approximateContributions:predictionInteractions:training:missingValue:)

Predict directly from array of floats, will build Data structure automatically with one row and features.count features.

Declaration

Swift

public func predict(
    features: FloatData,
    outputMargin: Bool = false,
    treeLimit: UInt32 = 0,
    predictionLeaf: Bool = false,
    predictionContributions: Bool = false,
    approximateContributions: Bool = false,
    predictionInteractions: Bool = false,
    training: Bool = false,
    missingValue: Float = Float.greatestFiniteMagnitude
) throws -> Float

Parameters

`features`	Features to base prediction at.
`outputMargin`	Whether to output the raw untransformed margin value.
`treeLimit`	Limit number of trees in the prediction. Zero means use all trees.
`predictionLeaf`	Each record indicating the predicted leaf index of each sample in each tree.
`predictionContributions`	Each record indicating the feature contributions (SHAP values) for that prediction.
`approximateContributions`	Approximate the contributions of each feature.
`predictionInteractions`	Indicate the SHAP interaction values for each pair of features.
`training`	Whether the prediction will be used for traning.
`missingValue`	Value in features representing missing values.


                    
                    
                    serialized()

Declaration

Swift

public func serialized() throws -> SerializedBuffer

Return Value

Everything states in buffer.


                    
                    
                    save(to:)

Saves modes into file.

Declaration

Swift

public func save(
    to path: String
) throws

Parameters

`to`	Path to output file.


                    
                    
                    raw()

Declaration

Swift

public func raw() throws -> RawModel

Return Value

Model as binary raw bytes.


                    
                    
                    dumped(features:featureMap:withStatistics:format:)

Dump model into a string.

Declaration

Swift

public func dumped(
    features: [Feature]? = nil,
    featureMap: String = "",
    withStatistics: Bool = false,
    format: ModelFormat = .text
) throws -> String

Parameters

`features`	Array of features.
`featureMap`	Name of the file containing feature map.
`withStatistics`	Controls whether the split statistics are output.
`format`	Desired output format type.

Return Value

Formated output into ModelFormat format.


                    
                    
                    rawDumped(features:featureMap:withStatistics:format:)

Dump model into an array of strings. In most cases you will want to use dumped method to get output in expected format.

Declaration

Swift

public func rawDumped(
    features: [Feature]? = nil,
    featureMap: String = "",
    withStatistics: Bool = false,
    format: ModelFormat = .text
) throws -> [String]

Parameters

`features`	Array of features, you can override ones stored in self.features with this.
`featureMap`	Name of the file containing feature map.
`withStatistics`	Controls whether the split statistics are output.
`format`	Desired output format type.

Return Value

Raw output from XGBoosterDumpModelEx provided as array of strings.


                    
                    
                    score(featureMap:importance:)

Get feature importance of each feature.

Declaration

Swift

public func score(
    featureMap: String = "",
    importance: Importance = .weight
) throws -> (features: [String: Int], gains: [String: Float]?)

Parameters

`featureMap`	Path to the feature map.
`importance`	Type of importance you want to compute.

Return Value

Tuple of features and gains, in case importance = weight, gains will be nil.


                    
                    
                    load(modelBuffer:)

Loads model from buffer.

Declaration

Swift

public func load(
    modelBuffer buffer: BufferModel
) throws

Parameters


                                model

Buffer to load from.


                    
                    
                    load(model:)

Loads model from file.

Declaration

Swift

public func load(
    model path: String
) throws

Parameters


                                model

Path of file to load model from.


                    
                    
                    load(config:)

Loads model from config.

Declaration

Swift

public func load(
    config: String
) throws

Parameters


                                model

Config to load from.


                    
                    
                    saveRabitCheckpoint()

Save the current checkpoint to rabit.

Declaration

Swift

public func saveRabitCheckpoint() throws


                    
                    
                    loadRabitCheckpoint()

Initialize the booster from rabit checkpoint.

Declaration

Swift

public func loadRabitCheckpoint() throws -> Int

Return Value

The output version of the model.


                    
                    
                    attribute(name:)

Get attribute string from the Booster.

Declaration

Swift

public func attribute(
    name: String
) throws -> String?

Parameters


                                name

Name of attribute to get.

Return Value

Value of attribute or nil if not set.


                    
                    
                    set(attribute:value:)

Set string attribute.

Declaration

Swift

public func set(
    attribute: String,
    value: String
) throws

Parameters

`attribute`	Name of attribute.
`value`	Value of attribute.


                    
                    
                    set(parameter:value:)

Set string parameter.

Declaration

Swift

public func set(
    parameter: String,
    value: String
) throws

Parameters

`parameter`	Name of parameter.
`value`	Value of parameter.


                    
                    
                    update(iteration:data:validateFeatures:)

Update for one iteration, with objective function calculated internally.

Declaration

Swift

public func update(
    iteration: Int,
    data: Data,
    validateFeatures: Bool = true
) throws

Parameters

`iteration`	Current iteration number.
`data`	Training data.
`validateFeatures`	Whether to validate features.


                    
                    
                    update(data:objective:validateFeatures:)

Update for one iteration with custom objective.

Declaration

Swift

public func update(
    data: Data,
    objective: ObjectiveFunction,
    validateFeatures: Bool = true
) throws

Parameters

`data`	Training data.
`objective`	Objective function returning gradient and hessian.
`validateFeatures`	Whether to validate features.


                    
                    
                    boost(data:gradient:hessian:validateFeatures:)

Boost the booster for one iteration, with customized gradient statistics.

Declaration

Swift

public func boost(
    data: Data,
    gradient: [Float],
    hessian: [Float],
    validateFeatures: Bool = true
) throws

Parameters

`data`	Training data.
`gradient`	The first order of gradient.
`hessian`	The second order of gradient.
`validateFeatures`	Whether to validate features.


                    
                    
                    evaluate(iteration:data:function:)

Evaluate array of data.

Declaration

Swift

public func evaluate(
    iteration: Int,
    data: [Data],
    function: EvaluationFunction? = nil
) throws -> [String: [String: String]]

Parameters

`iteration`	Current iteration.
`data`	Data to evaluate.
`function`	Custom function for evaluation.

Return Value

Dictionary in format [data_name: [eval_name: eval_value, …], …]


                    
                    
                    evaluate(iteration:data:function:)

Evaluate data.

Declaration

Swift

public func evaluate(
    iteration: Int,
    data: Data,
    function: EvaluationFunction? = nil
) throws -> [String: String]

Parameters

`iteration`	Current iteration.
`data`	Data to evaluate.
`function`	Custom function for evaluation.

Return Value

Dictionary in format [data_name: [eval_name: eval_value]]


                    
                    
                    validate(features:)

Validate features.

Declaration

Swift

public func validate(
    features: [Feature]
) throws

Parameters


                                features

Features to validate.


                    
                    
                    validate(data:)

Validate features.

Declaration

Swift

public func validate(
    data: DMatrix
) throws

Parameters


                                data

Data which features will be validated.


                    
                    
                    validate(data:)

Validate features.

Declaration

Swift

public func validate(
    data: [DMatrix]
) throws

Parameters


                                data

Array of data which features will be validated.


                    
                    
                    saveImportanceGraph(to:featureMap:importance:label:title:xAxisLabel:yAxisLabel:maxNumberOfFeatures:graphOrientation:enableGrid:size:renderer:)

Saves plot with importance based on fitted trees.

Declaration

Swift

public func saveImportanceGraph(
    to fileName: String,
    featureMap: String = "",
    importance: Importance = .weight,
    label: String = "Feature importance",
    title: String = "Feature importance",
    xAxisLabel: String = "Score",
    yAxisLabel: String = "Features",
    maxNumberOfFeatures: Int? = nil,
    graphOrientation: BarGraph<String, Float>.GraphOrientation = .horizontal,
    enableGrid: Bool = true,
    size: Size = Size(width: 1000, height: 660),
    renderer: Renderer = SVGRenderer()
) throws

Parameters

`to`	File where graph will be saved, .svg extension will be added if rendered remains SVGRenderer.
`featureMap`	Path to the feature map, if provided, replaces default f0, f1, … feature names.
`importance`	Type of importance to plot.
`label`	Label of graph.
`title`	Title of graph.
`xAxisLabel`	Label of X-axis.
`yAxisLabel`	Label of Y-axis.
`maxNumberOfFeatures`	Maximum number of top features displayed on plot. If None, all features will be displayed.
`graphOrientation`	Orientaton of ploted graph.
`enableGrid`	urn the axes grids on or off.
`size`	Size of ploted graph.
`renderer`	Renderer to use.


                    
                    
                    train(iterations:startIteration:trainingData:objectiveFunction:evaluationData:evaluationFunction:beforeIteration:callbacks:afterIteration:)

Train booster.

Declaration

Swift

public func train(
    iterations: Int,
    startIteration: Int? = nil,
    trainingData: Data,
    objectiveFunction: ObjectiveFunction? = nil,
    evaluationData: [Data] = [],
    evaluationFunction: EvaluationFunction? = nil,
    beforeIteration: BeforeIteration = DefaultBeforeIteration,
    callbacks: [Callback] = [],
    afterIteration: AfterIteration = DefaultAfterIteration
) throws

Parameters

`iterations`	Number of training iterations, but training can be stopped early.
`startIteration`	N. of starting iteration.
`trainingData`	Data to train on.
`evaluationData`	Data to evaluate on, if provided.
`evaluationFunction`	Custom evaluation function.
`beforeIteration`	Callback called before each iteration.
`callbacks`	Array of callbacks called at each iteration.
`afterIteration`	Callback called after each iteration.