So sánh phương pháp

	Sai số Tuyệt đối Trung bình (MAE)	Sai số bình phương trung bình (MSE)
Lĩnh vực	Đánh giá mô hình	Đánh giá mô hình
Họ	MCDM	MCDM
Năm ra đời	1799	1809
Người khởi xướng	Pierre-Simon Laplace	Carl Friedrich Gauss
Loại	Robust distance-based metric	Squared-error loss function
Công trình gốc	Laplace, P. S. (1799). Traité de Mécanique Céleste. Paris: J.B.M. Duprat.	Gauss, C. F. (1809). Theoria Motus Corporum Coelestium in Sectionibus Conicis Solem Ambientium. Hamburg: Perthes and Besser.
Tên gọi khác	MAE, L1 error, mean absolute deviation	MSE, L2 error, quadratic error
Liên quan	3	4
Tóm tắt	Mean Absolute Error is a robust metric that measures the average absolute magnitude of prediction errors in regression models. Dating back to Pierre-Simon Laplace's work on observational errors (1799), MAE quantifies typical prediction deviation by averaging the absolute differences between observed and predicted values.	Mean Squared Error is the foundational loss function for regression models, measuring the average squared deviation between predictions and observations. Originating from Gauss and Legendre's method of least squares (1805-1809), MSE is the basis for ordinary least squares regression and remains central to modern machine learning optimization.