evalml.pipelines.components.StackedEnsembleRegressor

class evalml.pipelines.components.StackedEnsembleRegressor(input_pipelines=None, final_estimator=None, cv=None, n_jobs=1, random_state=0, **kwargs)[source]

Stacked Ensemble Regressor.

name = 'Stacked Ensemble Regressor'
model_family = ('ensemble',)
supported_problem_types = [<ProblemTypes.REGRESSION: 'regression'>, <ProblemTypes.TIME_SERIES_REGRESSION: 'time series regression'>]
hyperparameter_ranges = {}
default_parameters = {'cv': None, 'final_estimator': None, 'n_jobs': 1}

Instance attributes

feature_importance

Not implemented for StackedEnsembleClassifier and StackedEnsembleRegressor

needs_fitting

parameters

Returns the parameters which were used to initialize the component

Methods:

__init__

Stacked ensemble regressor.

clone

Constructs a new component with the same parameters

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

Inheritance diagram of StackedEnsembleRegressor