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Multivariate Adaptive Regression Splines (MARS)×Beslutningstre×
FagfeltMaskinlæringMaskinlæring
FamilieMachine learningMachine learning
Opprinnelsesår19911984
OpphavspersonJerome H. FriedmanBreiman, Friedman, Olshen & Stone
TypeAdaptive piecewise-linear regressionRecursive partitioning (if-then rules)
Opprinnelig kildeFriedman, J. H. (1991). Multivariate adaptive regression splines. The Annals of Statistics, 19(1), 1–67. DOI ↗Breiman, L., Friedman, J.H., Olshen, R.A. & Stone, C.J. (1984). Classification and Regression Trees. Wadsworth. DOI ↗
Aliasmultivariate adaptive regression splines, earth algorithm, MARS regression, çok değişkenli uyarlamalı regresyon spline'larıKarar Ağacı (Decision Tree), karar ağacı, classification tree, regression tree
Relaterte45
SammendragMultivariate 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 Decision Tree is an interpretable classification and regression method, formalised by Breiman, Friedman, Olshen and Stone in their 1984 CART framework, that partitions the data with hierarchical if-then rules. Each split sends observations down one branch or another until a prediction is read off the leaf.
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ScholarGateSammenlign metoder: MARS · Decision Tree. Hentet 2026-06-15 fra https://scholargate.app/no/compare