Forecasting Class

Defines then names of forecasting algorithms used in automated ML.

Azure supports these regression algorithms, but you as a user do not need to specify the algorithms. 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

Inheritance

azureml.train.automl.constants.Regression

Forecasting

Constructor

Forecasting()

Attributes

Arimax

Arimax = 'Arimax'

AutoArima

AutoArima = 'AutoArima'

Average

Average = 'Average'

ExponentialSmoothing

ExponentialSmoothing = 'ExponentialSmoothing'

Naive

Naive = 'Naive'

Prophet

Prophet = 'Prophet'

SeasonalAverage

SeasonalAverage = 'SeasonalAverage'

SeasonalNaive

SeasonalNaive = 'SeasonalNaive'

TCNForecaster

TCNForecaster = 'TCNForecaster'