Initializer

init(trainingData:targetColumn:featureColumns:parameters:)

Creates a Random Forest Regressor from the feature columns in the training data to predict the values in the target column.

Declaration

init(trainingData: MLDataTable, targetColumn: String, featureColumns: [String]? = nil, parameters: MLRandomForestRegressor.ModelParameters = ModelParameters()) throws

Parameters

trainingData

A data table of training examples.

targetColumn

The column name for the values in the training data the regressor should predict.

featureColumns

The column names for the values in the training data that the regressor uses to predict the target value.

See Also

Creating and Training a Random Forest Regressor

struct MLRandomForestRegressor.ModelParameters

Parameters that affect the process of training a model.

let modelParameters: MLRandomForestRegressor.ModelParameters

The underlying parameters used when training the model.

var targetColumn: String

The name of the column you selected at initialization to define which feature the regressor predicts.

var featureColumns: [String]

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