So sánh phương pháp

	Phân tích phân biệt mạnh mẽ	Phân tích phân biệt bậc hai (QDA)
Lĩnh vực	Thống kê	Học máy
Họ	Regression model	Latent structure
Năm ra đời	1997	1939
Người khởi xướng	Hawkins & McLachlan (high-breakdown LDA); Croux & Dehon (S-estimator robust LDA)	Classical Gaussian discriminant analysis (Fisher / Welch lineage)
Loại	Robust classification / discriminant analysis	Generative Gaussian classifier
Công trình gốc	Hawkins, D. M. & McLachlan, G. J. (1997). High Breakdown Linear Discriminant Analysis. Journal of the American Statistical Association, 92(437), 136-143.	Hastie, T., Tibshirani, R., & Friedman, J. (2009). The Elements of Statistical Learning (2nd ed.). Springer. ISBN: 978-0-387-84857-0
Tên gọi khác	robust LDA, high-breakdown discriminant analysis, MCD-based discriminant analysis, Robust Diskriminant Analizi	QDA, quadratic classifier, kuadratik diskriminant analizi
Liên quan	5	2
Tóm tắt	Robust Discriminant Analysis is a classification method that separates groups with a linear discriminant function while resisting the influence of outliers. It replaces the classical mean and covariance with a high-breakdown estimator such as the Minimum Covariance Determinant (MCD), an approach developed by Hawkins & McLachlan (1997) and Croux & Dehon (2001).	Quadratic discriminant analysis is a generative classifier that models each class with its own multivariate Gaussian distribution, allowing each class a separate covariance matrix. Unlike linear discriminant analysis, which assumes a shared covariance and yields linear boundaries, QDA's per-class covariances produce curved (quadratic) decision boundaries, letting it capture differences in the spread and orientation of the classes.