evalml.pipelines.components.SimpleImputer

Inheritance diagram of SimpleImputer
class evalml.pipelines.components.SimpleImputer(impute_strategy='most_frequent', fill_value=None, random_state=0, **kwargs)[source]

Imputes missing data according to a specified imputation strategy.

name = 'Simple Imputer'
model_family = 'none'
hyperparameter_ranges = {'impute_strategy': ['mean', 'median', 'most_frequent']}
default_parameters = {'fill_value': None, 'impute_strategy': 'most_frequent'}

Instance attributes

needs_fitting

parameters

Returns the parameters which were used to initialize the component

Methods:

__init__

Initalizes an transformer that imputes missing data according to the specified imputation strategy.”

clone

Constructs a new component with the same parameters

describe

Describe a component and its parameters

fit

Fits imputer to data. ‘None’ values are converted to np.nan before imputation and are

fit_transform

Fits on X and transforms X :param X: Data to fit and transform :type X: pd.DataFrame :param y: Labels to fit and transform :type y: pd.

load

Loads component at file path

save

Saves component at file path

transform

Transforms data X by imputing missing values. ‘None’ values are converted to np.nan before imputation and are