So sánh phương pháp

	Hồi quy Spline Thích nghi Đa biến (MARS)	Mô hình cộng tính tổng quát (GAM)
Lĩnh vực	Học máy	Học máy
Họ	Machine learning	Machine learning
Năm ra đời	1991	1986
Người khởi xướng	Jerome H. Friedman	Trevor Hastie & Robert Tibshirani
Loại	Adaptive piecewise-linear regression	Semi-parametric additive regression model
Công trình gốc	Friedman, J. H. (1991). Multivariate adaptive regression splines. The Annals of Statistics, 19(1), 1–67.	Hastie, T., & Tibshirani, R. (1986). Generalized additive models. Statistical Science, 1(3), 297–310.
Tên gọi khác	multivariate adaptive regression splines, earth algorithm, MARS regression, çok değişkenli uyarlamalı regresyon spline'ları	GAM, additive model, spline-based additive regression, Genelleştirilmiş toplamsal model
Liên quan	4	4
Tóm tắt	Multivariate adaptive regression splines, introduced by Jerome Friedman in 1991, is a flexible nonparametric regression method that automatically models nonlinearities and interactions by combining piecewise-linear 'hinge' functions. It builds the model in a forward stagewise pass that adds basis functions where they help most, then prunes back the overgrown model, yielding an interpretable additive-plus-interaction form that adapts its complexity to the data.	A generalized additive model, introduced by Trevor Hastie and Robert Tibshirani in 1986, extends the generalized linear model by replacing each linear term with a smooth, data-driven function of the predictor. This lets the model capture nonlinear relationships while preserving the additive, term-by-term interpretability of regression: each predictor contributes its own estimated curve, and the curves simply add up (on a link scale) to predict the response.