So sánh phương pháp

	Hệ số xác định hiệu chỉnh (R²_adj)	Tiêu chí Thông tin Akaike (AIC)
Lĩnh vực	Đánh giá mô hình	Đánh giá mô hình
Họ	MCDM	MCDM
Năm ra đời	1961	1974
Người khởi xướng	Henri Theil	Hirotugu Akaike
Loại	Penalized goodness-of-fit metric	Model selection metric
Công trình gốc	Theil, H. (1961). Economic Forecasts and Policy. Amsterdam: North-Holland Publishing Company.	Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19(6), 716-723.
Tên gọi khác	Adjusted R², R²_adj	AIC
Liên quan	5	4
Tóm tắt	Adjusted R² is a corrected version of the coefficient of determination that accounts for the number of predictors in a regression model. Introduced by Henri Theil in 1961, it addresses the fundamental limitation of standard R²: the tendency to increase whenever any predictor is added, regardless of whether that predictor contributes meaningfully to explaining the target variable.	The Akaike Information Criterion is an information-theoretic measure for model selection that balances goodness of fit against model complexity. Introduced by Hirotugu Akaike in 1974, AIC estimates the relative quality of models for a given dataset, penalizing additional parameters to prevent overfitting.