From the course: Machine Learning with Python: Decision Trees
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How is a regression tree built? - Python Tutorial
From the course: Machine Learning with Python: Decision Trees
How is a regression tree built?
- [Instructor] Similar to classification trees, regression trees are built using a process known as recursive partitioning. For regression trees, the objective of recursive partitioning is to create successive child partitions that have less variability than their parent. To illustrate how recursive partitioning helps us build a regression tree, let's imagine that we work for a placement agency and that we just received the results of an income survey conducted by our agency. Each survey response includes the age of the worker, their level of education or highest degree earned, and their annual salary. Note that age and education level are the independent variables, or predictors, while salary is the dependent variable. Each of the survey responses can be represented on the scatter plot this way in terms of the dependent variable, annual salary, and one of the independent variables, age. Recall that for regression…
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