Entropy and information gain in Machine Learning
In machine learning, entropy and information gain are fundamental concepts used in decision trees and supervised learning to make data division decisions during the training process of a model. These concepts are often associated with the Iterative Dichotomiser 3 (ID3) algorithm and its variants, such as