Classification And Regression Trees for Machine Learning
Last Updated on August 15, 2020
Decision Trees are an important type of algorithm for predictive modeling machine learning.
The classical decision tree algorithms have been around for decades and modern variations like random forest are among the most powerful techniques available.
In this post you will discover the humble decision tree algorithm known by it’s more modern name CART which stands for Classification And Regression Trees. After reading this post, you will know:
- The many names used to describe the CART algorithm for machine learning.
- The representation used by learned CART models that is actually stored on disk.
- How a CART model can be learned from training data.
- How a learned CART model can be used to make predictions on unseen data.
- Additional resources that you can use to learn more about CART and related algorithms.
If you have taken an algorithms and data structures course, it might be hard to hold you back from implementing this simple and powerful algorithm. And from there, you’re a small step away from your own implementation of Random Forests.
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