evalml.pipelines.components.BaselineRegressor

class evalml.pipelines.components.BaselineRegressor(strategy='mean', random_state=0, **kwargs)

Regressor that predicts using the specified strategy.

This is useful as a simple baseline regressor to compare with other regressors.

name = 'Baseline Regressor'

model_family = 'baseline'

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

hyperparameter_ranges = {}

default_parameters = {'strategy': 'mean'}

predict_uses_y = False

Instance attributes

feature_importance	Returns importance associated with each feature.
needs_fitting
parameters	Returns the parameters which were used to initialize the component

Methods:

__init__	Baseline regressor that uses a simple strategy to make predictions.
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.XGBoostRegressor.save evalml.pipelines.components.BaselineRegressor.__init__