AI engineering glossary · Classical ML algorithms
What is gini impurity?
Gini impurity (also called Gini index): A measure of how mixed the classes are in a group of examples: 1 minus the sum of squared class proportions. It is 0 when all items share one class and highest when classes are evenly mixed. Tree building picks splits that reduce it the most.
Gini impurity: an example
A node with 6 spam and 4 not-spam emails has Gini = 1 - (0.6^2 + 0.4^2) = 0.48.
Related terms
More Classical ML algorithms terms
Where you learn it
Gini impurity is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.