Σύγκριση μεθόδων

	Ελαχίστη Εκατοστιαία Τετραγωνικών Καταλοίπων (LMS) Παλινδρόμηση	Παλινδρόμηση RANSAC
Πεδίο	Στατιστική	Στατιστική
Οικογένεια	Regression model	Regression model
Έτος προέλευσης	1984	1981
Δημιουργός	Peter J. Rousseeuw	Fischler & Bolles
Τύπος	Robust linear regression	Robust linear regression
Θεμελιώδης πηγή	Rousseeuw, P. J. (1984). Least Median of Squares Regression. Journal of the American Statistical Association, 79(388), 871-880.	Fischler, M. A. & Bolles, R. C. (1981). Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. Communications of the ACM, 24(6), 381-395.
Εναλλακτικές ονομασίες	LMS, least median of squares regression, en küçük medyan kareler (LMS)	random sample consensus, RANSAC, robust regression, RANSAC Regresyonu
Συναφείς	5	5
Σύνοψη	Least Median of Squares is a robust linear regression method introduced by Peter J. Rousseeuw in 1984. Instead of minimising the sum of squared residuals like ordinary least squares, it minimises the median of the squared residuals, which lets the fit resist contamination by up to roughly 50% outliers.	RANSAC Regression is a robust linear regression method introduced by Fischler and Bolles in 1981 that fits a model to the inlier points of a dataset while automatically excluding outliers. Instead of fitting all the data at once, it repeatedly samples small subsets, fits a candidate model, and keeps the model that wins the largest consensus of agreeing points.