Advantages and Disadvantages of Trees (C.h 8.1.4)
- Pro: Trees are very easy to explain to people. In fact, they are even easier to explain than linear regression!
- Pro: Some people believe that decision trees more closely mirror human decision-making than do the regression and classification approaches seen in previous chapters.
- Pro: Trees can be displayed graphically, and are easily interpreted even by a non-expert (especially if they are small).
- Pro: Trees can easily handle qualitative predictors without the need to create dummy variables.
- Contra: Unfortunately, trees generally do not have the same level of predictive accuracy as some of the other regression and classification approaches seen in this book.
- Contra: Additionally, trees can be very non-robust. In other words, a small change in the data can cause a large change in the final estimated tree.