evalml.pipelines.components.OneHotEncoder

class evalml.pipelines.components.OneHotEncoder(top_n=10, features_to_encode=None, categories=None, drop=None, handle_unknown='ignore', handle_missing='error', random_state=None, random_seed=0, **kwargs)

One-hot encoder to encode non-numeric data.

name = 'One Hot Encoder'

model_family = 'none'

hyperparameter_ranges = {}

default_parameters = {'categories': None, 'drop': None, 'features_to_encode': None, 'handle_missing': 'error', 'handle_unknown': 'ignore', 'top_n': 10}

Instance attributes

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

Methods:

__init__	Initalizes an transformer that encodes categorical features in a one-hot numeric array.”
categories	Returns a list of the unique categories to be encoded for the particular feature, in order.
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 categorical features after fitting.
load	Loads component at file path
save	Saves component at file path
transform	One-hot encode the input data.

Class Inheritance

evalml.pipelines.components.SelectColumns.transform evalml.pipelines.components.OneHotEncoder.__init__