We fill/impute missing values using the following methods. Or make missing values as a separate category.
Mean Imputation for Continuous Variables (No Outlier)
Median Imputation for Continuous Variables (If Outlier)
Cluster Imputation for Continuous Variables
Imputation with a random value that is drawn between the minimum and maximum of the variable [Random value = min(x) + (max(x) - min(x)) * ranuni(SEED)]
Impute Continuous Variables with Zero (Require business knowledge)
Conditional Mean Imputation for Continuous Variables
Other Imputation Methods for Continuous - Predictive mean matching, Bayesian linear regression, Linear regression ignoring model error etc.
WOE for missing values in categorical variables
