How does a Decision Tree handle missing values?
Updated May 16, 2026
Short answer
Decision Trees handle missing values by surrogate splits or data imputation strategies.
Deep explanation
Some implementations split based on available data or assign missing values to the most probable branch. Others use surrogate splits or preprocessing imputation techniques.
Real-world example
Used in healthcare datasets where patient data is often incomplete.
Common mistakes
- Assuming Decision Trees automatically handle all missing values.
Follow-up questions
- What is surrogate splitting?
- Should we always impute data?