What are the disadvantages and advantages of using a Decision Tree?

Following are the advantages of Decision Trees:

1. They are able to identify and model complex patterns.
2. Work well with both classification and regression problems
3. Unaffected by outliers
4. Easier to explain to non technical stakeholders. Complex Decision Trees can be explained just by creating their visual representations.
5. Scaling and normalization are not needed

Following are the disadvantages of Decision Trees:

1. Sensitive to overfitting
2. Small change in data can cause instability in the model owing to use of recursive binary splitting
3. They are computationally more intensive and take longer time to train than other classification algorithms.