Advantages vs Disadvantages of Decision trees?

Advantages: • White-box method, totally transparent • Small data preparation (can deal with categorical and numerical data, no scaling needed..) • Robust against missing data • Non-linearity Disadvantages: • High variance algorithm. Small changes in input data can lead to very different trees. Prone to overfit • Can have problems with unbalanced data • Poorly suited for regression • Greedy algorithm