evalml.pipelines.components.ARIMARegressor

class evalml.pipelines.components.ARIMARegressor(date_index=None, trend=None, start_p=2, d=0, start_q=2, max_p=5, max_d=2, max_q=5, seasonal=True, n_jobs=- 1, random_seed=0, **kwargs)

Autoregressive Integrated Moving Average Model. The three parameters (p, d, q) are the AR order, the degree of differencing, and the MA order. More information here: https://www.statsmodels.org/devel/generated/statsmodels.tsa.arima_model.ARIMA.html

Currently ARIMARegressor isn’t supported via conda install. It’s recommended that it be installed via PyPI.

name = 'ARIMA Regressor'

model_family = 'arima'

supported_problem_types = [<ProblemTypes.TIME_SERIES_REGRESSION: 'time series regression'>]

hyperparameter_ranges = {'d': Integer(low=0, high=2, prior='uniform', transform='identity'), 'max_d': Integer(low=2, high=5, prior='uniform', transform='identity'), 'max_p': Integer(low=3, high=10, prior='uniform', transform='identity'), 'max_q': Integer(low=3, high=10, prior='uniform', transform='identity'), 'seasonal': [True, False], 'start_p': Integer(low=1, high=3, prior='uniform', transform='identity'), 'start_q': Integer(low=1, high=3, prior='uniform', transform='identity')}

default_parameters = {'d': 0, 'date_index': None, 'max_d': 2, 'max_p': 5, 'max_q': 5, 'n_jobs': -1, 'seasonal': True, 'start_p': 2, 'start_q': 2, 'trend': None}

predict_uses_y = False

Instance attributes

feature_importance	Returns array of 0’s with a length of 1 as feature_importance is not defined for ARIMA regressor.
needs_fitting
parameters	Returns the parameters which were used to initialize the component

Methods:

__init__	param date_index Specifies the name of the column in X that provides the datetime objects. Defaults to None.
clone	Constructs a new component with the same parameters and random state.
describe	Describe a component and its parameters
fit	Fits component to data
load	Loads component at file path
predict	Make predictions using selected features.
predict_proba	Make probability estimates for labels.
save	Saves component at file path

Class Inheritance

evalml.pipelines.components.SVMClassifier.save evalml.pipelines.components.ARIMARegressor.__init__