evalml.pipelines.components.PerColumnImputer

Inheritance diagram of PerColumnImputer
class evalml.pipelines.components.PerColumnImputer(impute_strategies=None, default_impute_strategy='most_frequent', random_state=0, **kwargs)[source]

Imputes missing data according to a specified imputation strategy per column

name = 'Per Column Imputer'
model_family = 'none'
hyperparameter_ranges = {}
default_parameters = {'default_impute_strategy': 'most_frequent', 'impute_strategies': None}

Instance attributes

needs_fitting

parameters

Returns the parameters which were used to initialize the component

Methods:

__init__

Initializes a transformer that imputes missing data according to the specified imputation strategy per column.”

clone

Constructs a new component with the same parameters

describe

Describe a component and its parameters

fit

Fits imputers on data X

fit_transform

Fits imputer on data X then imputes missing values in X

load

Loads component at file path

save

Saves component at file path

transform

Transforms data X by imputing missing values