We fill/impute missing values using the following METHODS. Or make missing values as a separate category.

1. Mean Imputation for CONTINUOUS Variables (No Outlier)
2. Median Imputation for Continuous Variables (If Outlier)
3. Cluster Imputation for Continuous Variables
4. 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)]
5. Impute Continuous Variables with ZERO (Require business knowledge)
6. Conditional Mean Imputation for Continuous Variables
7. Other Imputation Methods for Continuous - Predictive mean matching, Bayesian linear regression, Linear regression ignoring model error etc.
8. WOE for missing values in CATEGORICAL variables
9. Decision Tree, Random Forest, Logistic Regression for Categorical Variables
10. Decision Tree, Random Forest WORKS for both Continuous and Categorical Variables
11. Multiple Imputation Method

We fill/impute missing values using the following methods. Or make missing values as a separate category.