Learning Predictive Analytics with Python

Understanding and implementing regression trees

An algorithm very similar to decision trees is regression tree. The difference between the two is that the target variable in the case of a regression tree is a continuous numerical variable, unlike decision trees where the target variable is a categorical variable.

Regression tree algorithm

Regression trees are particularly useful when there are multiple features in the training dataset that interact in complicated and non-linear ways. In such cases, a simple linear regression or even the linear regression with some tweaks will not be feasible or produces a very complex model that will be of little use. An alternative to non-linear regression is to partition the dataset into smaller nodes/local partitions ...