evalml.pipelines.components.Imputer.__init__

Imputer.__init__(categorical_impute_strategy='most_frequent', numeric_impute_strategy='mean', fill_value=None, random_state=0, **kwargs)

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

Parameters

• categorical_impute_strategy (string) – Impute strategy to use for string, object, boolean, categorical dtypes. Valid values include “most_frequent” and “constant”.

• numeric_impute_strategy (string) – Impute strategy to use for numeric dtypes. Valid values include “mean”, “median”, “most_frequent”, and “constant”.

• fill_value (string) – When impute_strategy == “constant”, fill_value is used to replace missing data. Defaults to 0 when imputing data and “missing_value” for strings or object data types.

evalml.pipelines.components.Imputer evalml.pipelines.components.Imputer.clone