Hands-On Machine Learning for Algorithmic Trading

Strengths and weaknesses of decision trees

Regression and classification trees take a very different approach to prediction when compared to the linear models we have explored so far. How do you decide which model is more suitable to the problem at hand? Consider the following:

• If the relationship between the outcome and the features is approximately linear (or can be transformed accordingly), then linear regression will likely outperform a more complex method, such as a decision tree that does not exploit this linear structure.
• If the relationship appears highly non-linear and more complex, decision trees will likely outperform the classical models.

Several advantages have made decision trees very popular:

• They are fairly straightforward ...