evalml.pipelines.components.TargetEncoder

class evalml.pipelines.components.TargetEncoder(cols=None, smoothing=1.0, handle_unknown='value', handle_missing='value', random_seed=0, **kwargs)

Target encoder to encode categorical data

name = 'Target Encoder'

model_family = 'none'

hyperparameter_ranges = {}

default_parameters = {'cols': None, 'handle_missing': 'value', 'handle_unknown': 'value', 'smoothing': 1.0}

Instance attributes

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

Methods:

__init__	Initializes a transformer that encodes categorical features into target encodings.
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	Return feature names for the input features after fitting.
load	Loads component at file path
save	Saves component at file path
transform	Transforms data X.

Class Inheritance

evalml.pipelines.components.OneHotEncoder.transform evalml.pipelines.components.TargetEncoder.__init__