Сравнение на методи

	Графика на лифт и гейн	Прецизност-Отзивчивост AUC
Област	Оценка на модели	Оценка на модели
Семейство	MCDM	MCDM
Година на възникване	1990s	2006
Създател	Data mining and marketing analytics	Davis and Goadrich
Тип	Evaluation visualization	Evaluation metric
Основополагащ източник	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.
Други названия	Cumulative Gain Chart, Lift Curve	PR AUC, PR Curve
Свързани	2	4
Резюме	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.