Class balance refers to the relative distribution of the number of examples among different classes. In machine learning and data-related tasks, models typically achieve better performance when the number of examples for each class is relatively balanced. When the number of examples of a specific class is disproportionately low, this class is said to be "under-represented." Conversely, if a particular class has a significantly larger number of instances compared to others, it is considered "over-represented."
