विधियों की तुलना करें

	लिफ्ट और गेन चार्ट	प्रिसिजन-रिकॉल एयूसी
क्षेत्र	मॉडल मूल्यांकन	मॉडल मूल्यांकन
परिवार	MCDM	MCDM
उद्भव वर्ष	1990s	2006
प्रवर्तक	Data mining and marketing analytics	Davis and Goadrich
प्रकार	Evaluation visualization	Evaluation metric
मौलिक स्रोत	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.
उपनाम	Cumulative Gain Chart, Lift Curve	PR AUC, PR Curve
संबंधित	2	4
सारांश	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.