evalml.pipelines.components.DateTimeFeaturizer

class evalml.pipelines.components.DateTimeFeaturizer(features_to_extract=None, encode_as_categories=False, random_state=None, random_seed=0, **kwargs)[source]

Transformer that can automatically featurize DateTime columns.

name = 'DateTime Featurization Component'
model_family = 'none'
hyperparameter_ranges = {}
default_parameters = {'encode_as_categories': False, 'features_to_extract': ['year', 'month', 'day_of_week', 'hour']}

Instance attributes

needs_fitting

parameters

Returns the parameters which were used to initialize the component

Methods:

__init__

Extracts features from DateTime columns

clone

Constructs a new component with the same parameters and random state.

describe

Describe a component and its parameters

fit

Fits component to data

fit_transform

Fits on X and transforms X

get_feature_names

Gets the categories of each datetime feature.

load

Loads component at file path

save

Saves component at file path

transform

Transforms data X by creating new features using existing DateTime columns, and then dropping those DateTime columns

Class Inheritance

Inheritance diagram of DateTimeFeaturizer