Also known as: Class balanced Dataset
Сбалансированный по классам набор данных — набор данных, в котором примеры распределены примерно равномерно по целевым классам. Сбалансированное представление классов может делать обучение и оценку модели более стабильными, особенно когда важны миноритарные классы.
A dataset containing categorical labels in which the number of instances of each category is approximately equal. For example, consider a botanical dataset whose binary label can be either native plant or nonnative plant: - A dataset with 515 native plants and 485 nonnative plants is a class-balanced dataset. - A dataset with 875 native plants and 125 nonnative plants is a class-imbalanced dataset. A formal dividing line between class-balanced datasets and class-imbalanced datasets doesn't exist. The distinction only becomes important when a model trained on a highly class-imbalanced dataset can't converge. See Datasets: imbalanced datasets in Machine Learning Crash Course for details.