Сравнение методов

	График лифта и прироста	Precision-Recall AUC
Область	Оценка моделей	Оценка моделей
Семейство	MCDM	MCDM
Год появления	1990s	2006
Автор метода	Data mining and marketing analytics	Davis and Goadrich
Тип	Evaluation visualization	Evaluation metric
Основополагающий источник	Maimon, O. Z., & Rokach, L. (Eds.). (2010). Data Mining and Knowledge Discovery Handbook (2nd ed.). Springer.	Davis, J., & Goadrich, M. (2006). The relationship between precision-recall and ROC curves. Proceedings of the 23rd International Conference on Machine Learning, 233-240.
Другие названия	Cumulative Gain Chart, Lift Curve	PR AUC, PR Curve
Связанные	2	4
Сводка	Lift and gain charts visualize classifier performance by showing how much better the model performs compared to random selection, particularly useful for ranking or scoring tasks where you select a top percentage of samples. They are widely used in marketing, credit scoring, and fraud detection.	The Precision-Recall Area Under the Curve (PR AUC) is the area under the curve formed by plotting recall on the x-axis and precision on the y-axis. It is particularly useful for evaluating classifiers on imbalanced datasets, where it is often more informative than ROC AUC.