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Machine Learning in Action by Peter Harrington

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Chapter 9. Tree-based regression

 

This chapter covers
  • The CART algorithm
  • Regression and model trees
  • Tree-pruning algorithms
  • Building a GUI in Python

 

The linear regression methods we looked at in chapter 8 contain some powerful methods. These methods create a model that needs to work for all of the data points (locally weighted linear regression is the exception). When the data has many features that interact in complicated ways, building a global model can be difficult if not foolish. We know there are many nonlinearities in real life. How can we expect to model everything with a global linear model?

One way to build a model for our data is to subdivide the data into sections that can be modeled easily. These partitions can then be modeled ...

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