evalml.pipelines.components.DelayedFeatureTransformer.init¶

DelayedFeatureTransformer.__init__(max_delay=2, delay_features=True, delay_target=True, gap=1, random_state=0, **kwargs)[source]¶

Creates a DelayedFeatureTransformer.

Parameters

max_delay (int) – Maximum number of time units to delay each feature.
delay_features (bool) – Whether to delay the input features.
delay_target (bool) – Whether to delay the target.
gap (int) – The number of time units between when the features are collected and when the target is collected. For example, if you are predicting the next time step’s target, gap=1. This is only needed because when gap=0, we need to be sure to start the lagging of the target variable at 1.
random_state (int, np.random.RandomState) – Seed for the random number generator. There is no randomness in this transformer.

evalml.pipelines.components.DelayedFeatureTransformer.__init__¶