A regressor that estimates the target as a linear function of the features.
SDKs
- macOS 10.14+
- Xcode 10.0+
Framework
- Create ML
Declaration
struct MLLinearRegressor
StructureMLLinear
MLLinear
Topics
Creating and Training a Linear Regressor
init(trainingCreates a Linear Regressor from the feature columns in the training data to predict the values in the target column.
struct MLLinearParameters that affect the process of training a model.
let modelThe underlying parameters used when training the model.
var targetThe name of the column you selected at initialization to define which feature the regressor predicts.
var featureThe names of the columns you selected at initialization to train the regressor.
Assessing Model Accuracy
var trainingMeasurements of the regressor’s performance on the training data set.
var validationMeasurements of the regressor’s performance on the validation data set.
Evaluating a Linear Regressor
func evaluation(on: MLDataReturns metrics describing the regressor’s performance on the provided labeled data.
Testing a Linear Regressor
func predictions(from: MLDataPredicts the target value from the provided data.
Saving a Linear Regressor
func write(to: URL, metadata: MLModelExports a Core ML model file for use in your app.
func write(toExports a Core ML model file for use in your app.
Describing a Linear Regressor
var model: MLModelThe underlying Core ML model stored in memory.
var description: StringA text representation of the linear regressor.
var debugA text representation of the linear regressor that’s suitable for output during debugging.
var playgroundA description of the linear regressor shown in a playground.
Relationships
See Also
Supporting Regressor Types
struct MLDecisionA regressor that estimates the target by learning rules to split the data.
struct MLRandomA regressor based on a collection of decision trees trained on subsets of the data.
struct MLBoostedA regressor based on a collection of decision trees combined with gradient boosting.