Missing Data Imputer

SimpleImputer/IterativeImputer/KNNImputer

Common

Input Data

	Inputs
*Target Data	Data input
*Output Name	Name of the cleansed data after imputation
*Imputer	Name of the user-defined imputer module
*x	Columns (variables) to be cleansed by the imputer Columns should be correctly formatted for the user-defined imputation method. Data type: SimpleImputer: all data type, else: numeric. One or more columns should be selected.

Variable Attributes

• Data Type : Data type of the column (variable); e.g) int64, float64, Object, etc.

• Missing: # of missing values in the column (variable).

[Task information of IterativeImputer]

Python Package

SimpleImputer: https://scikit-learn.org/stable/modules/generated/sklearn.impute.SimpleImputer.html

IterativeImputer: https://scikit-learn.org/stable/modules/generated/sklearn.impute.IterativeImputer.html

KNNImputer: https://scikit-learn.org/stable/modules/generated/sklearn.impute.KNNImputer.html