পদ্ধতির তুলনা করুন

	লিফট এবং গেইন চার্ট	প্রিসিশন-রিকল এউসি (Precision-Recall AUC)
ক্ষেত্র	মডেল মূল্যায়ন	মডেল মূল্যায়ন
পরিবার	MCDM	MCDM
উদ্ভবের বছর	1990s	2006
প্রবর্তক	Data mining and marketing analytics	Davis and Goadrich
ধরন	Evaluation visualization	Evaluation metric
মৌলিক উৎস	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.
অপর নাম	Cumulative Gain Chart, Lift Curve	PR AUC, PR Curve
সম্পর্কিত	2	4
সারসংক্ষেপ	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.