Lecture 6 - CART vs ID3

Lecture 6 - CART vs ID3

di LUIGI BORRIELLO -
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Key differences between CART (used in SKlearn) and ID3 are:

  1. Type of learning:

    • ID3, as an "Iterative Dichotomiser," is for binary classification only
    • CART, or "Classification And Regression Trees," is a family of algorithms (including, but not limited to, binary classification tree learning). 
  2. Loss functions used for split selection.

    • ID3, selects its splits based on Information Gain, which is the reduction in entropy between the parent node and (weighted sum of) children nodes.
    • CART, when used for classification, selects its splits to achieve the subsets that minimize Gini Impurity.