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Introduction To Tree-Based ML Methods

Gradient boosting, decision trees, and random forests are some of the tree-based methods covered in this lesson.

Numeric and categorical outputs are predicted with tree-based learning algorithms, also known as CART.

Boosting, bagging, random forests, decision trees, and other tree-based methods have been proven to be very effective for supervised learning. Moreover, they can predict both discrete and continuous outcomes, which explains their high accuracy.

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Onepagecode

Onepagecode

Studied cs from uni of essex. I like ML and DS.