evalml.pipelines.components.DelayedFeatureTransformer

class evalml.pipelines.components.DelayedFeatureTransformer(date_index=None, max_delay=2, delay_features=True, delay_target=True, gap=1, random_seed=0, **kwargs)

Transformer that delayes input features and target variable for time series problems.

name = 'Delayed Feature Transformer'

model_family = 'none'

hyperparameter_ranges = {}

default_parameters = {'date_index': None, 'delay_features': True, 'delay_target': True, 'gap': 1, 'max_delay': 2}

Instance attributes

needs_fitting
parameters	Returns the parameters which were used to initialize the component

Methods:

__init__	Creates a DelayedFeatureTransformer.
clone	Constructs a new component with the same parameters and random state.
describe	Describe a component and its parameters
fit	Fits the DelayFeatureTransformer.
fit_transform	Fits on X and transforms X
load	Loads component at file path
save	Saves component at file path
transform	Computes the delayed features for all features in X and y.

Class Inheritance

evalml.pipelines.components.TextFeaturizer.transform evalml.pipelines.components.DelayedFeatureTransformer.__init__