Advantages and Disadvantages of Decision Trees

Pros:

Easy to explain to people, even easier to explain than linear regression!
Can be displayed graphically, and are easily interpreted even by non-expert(especially if they are small)
Easily handle Qualitative Predictors without the need to create dummy variables.
Handle missing data
Easily handle irrelevant attributes
Very fast
Handel non-linear features
Built in to take into account variable interactions
Intuitive Decision rules

Cons:
Only axis aligned splits of data - dicision boundary linear can't model
greedy
Low Bias, High Variance
No ranking score as direct result