---
title: "makeTrainingSession(trainingData:targetColumn:featureColumns:parameters:sessionParameters:)"
framework: createml
role: symbol
role_heading: Type Method
path: "createml/mldecisiontreeregressor/maketrainingsession(trainingdata:targetcolumn:featurecolumns:parameters:sessionparameters:)"
---

# makeTrainingSession(trainingData:targetColumn:featureColumns:parameters:sessionParameters:)

Creates or restores a training session.

## Declaration

```swift
static func makeTrainingSession(trainingData: DataFrame, targetColumn: String, featureColumns: [String]? = nil, parameters: MLDecisionTreeRegressor.ModelParameters = .init(validation: .split(strategy: .automatic)), sessionParameters: MLTrainingSessionParameters = _defaultSessionParameters) throws -> MLTrainingSession<MLDecisionTreeRegressor>
```

## Parameters

- `trainingData`: A DataFrame specifying training data.
- `targetColumn`: A String specifying the target column name in the trainingData
- `featureColumns`: An optional list of Strings specifying feature columns to be used to predict the target, if not provided, default to use all the other columns in the trainingData, except the one specified by targetColumn
- `parameters`: Model training parameters. See doc://com.apple.createml/documentation/CreateML/MLDecisionTreeRegressor/ModelParameters-swift.struct for the defaults.
- `sessionParameters`: Training session parameters. See doc://com.apple.createml/documentation/CreateML/MLTrainingSessionParameters for the defaults.

## Return Value

Return Value A MLTrainingSession that can be used to start or resume training.

## See Also

### Training a decision tree regressor asynchronously

- [train(trainingData:targetColumn:featureColumns:parameters:sessionParameters:)](createml/mldecisiontreeregressor/train(trainingdata:targetcolumn:featurecolumns:parameters:sessionparameters:).md)
- [resume(_:)](createml/mldecisiontreeregressor/resume(_:).md)
- [restoreTrainingSession(sessionParameters:)](createml/mldecisiontreeregressor/restoretrainingsession(sessionparameters:).md)