What is the difference between CART, ID3, and C4.5 algorithms?

CART uses binary splits and Gini, ID3 uses entropy, and C4.5 improves ID3 with gain ratio and pruning.

ID3 builds trees using information gain and handles only categorical features. C4.5 extends ID3 by handling continuous features, missing values, and uses gain ratio to reduce bias toward high-cardinality features. CART (used in sklearn) always produces binary trees and supports both classification and regression using Gini impurity or MSE. CART is widely used in production due to efficiency and simplicity.