Structure

MLDecisionTreeClassifier.ModelParameters

Parameters that affect the process of training a model.

Declaration

struct MLDecisionTreeClassifier.ModelParameters

Topics

Accessing Parameters

var validationData: MLDataTable?

The data used for the validation set to inform the model training process.

Deprecated
var maxDepth: Int

The maximum depth of the tree. Must be greater than 0.

var minLossReduction: Double

The minimum amount that the loss needs to be reduced to create a new split.

var minChildWeight: Double

The minimum weight of each leaf node.

var randomSeed: Int

The seed value for random operations during tree building process.

Describing Parameters

var description: String

A text representation of the model parameters for a decision tree classifier.

var debugDescription: String

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

var playgroundDescription: Any

A description of the model parameters for a decision tree classifier shown in a playground.

See Also

Creating and Training a Model

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

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