Regression Class

Defines the names of regression algorithms used in automated ML.

Azure supports these regression algorithms, but you as a user do not need to specify the algorithms directly. Use the allowed_models and blocked_models parameters of AutoMLConfig class to include or exclude models.

To learn more about in automated ML in Azure see:

• What is automated ML

• How to define a machine learning task

• Configure automated ML experiments in Python

• TensorFlowDNN, TensorFlowLinearRegressor are deprecated.

Inheritance

builtins.object

Regression

Constructor

Regression()

Attributes

DecisionTreeRegressor

DecisionTreeRegressor = 'DecisionTree'

ElasticNet

ElasticNet = 'ElasticNet'

ExtraTreesRegressor

ExtraTreesRegressor = 'ExtremeRandomTrees'

FastLinearRegressor

FastLinearRegressor = 'FastLinearRegressor'

GradientBoostingRegressor

GradientBoostingRegressor = 'GradientBoosting'

KNearestNeighborsRegressor

KNearestNeighborsRegressor = 'KNN'

LassoLars

LassoLars = 'LassoLars'

LightGBMRegressor

LightGBMRegressor = 'LightGBM'

OnlineGradientDescentRegressor

OnlineGradientDescentRegressor = 'OnlineGradientDescentRegressor'

RandomForestRegressor

RandomForestRegressor = 'RandomForest'

SGDRegressor

SGDRegressor = 'SGD'

TabNetRegressor

TabNetRegressor = 'TabnetRegressor'

TensorFlowDNNRegressor

TensorFlowDNNRegressor = 'TensorFlowDNN'

TensorFlowLinearRegressor

TensorFlowLinearRegressor = 'TensorFlowLinearRegressor'

XGBoostRegressor

XGBoostRegressor = 'XGBoostRegressor'