evalml.pipelines.components.TimeSeriesBaselineEstimator

class evalml.pipelines.components.TimeSeriesBaselineEstimator(gap=1, random_state=0, **kwargs)

Time series estimator that predicts using the naive forecasting approach.

This is useful as a simple baseline estimator for time series problems

name = 'Time Series Baseline Estimator'

model_family = 'baseline'

supported_problem_types = [<ProblemTypes.TIME_SERIES_REGRESSION: 'time series regression'>, <ProblemTypes.TIME_SERIES_BINARY: 'time series binary'>, <ProblemTypes.TIME_SERIES_MULTICLASS: 'time series multiclass'>]

hyperparameter_ranges = {}

default_parameters = {'gap': 1}

predict_uses_y = True

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 time series estimator that predicts using the naive forecasting approach.
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.BaselineRegressor.save evalml.pipelines.components.TimeSeriesBaselineEstimator.__init__