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| Multivariate Adaptive Regression Splines (MARS)× | Beslutsträd× | |
|---|---|---|
| Ämnesområde | Maskininlärning | Maskininlärning |
| Familj | Machine learning | Machine learning |
| Ursprungsår≠ | 1991 | 1984 |
| Upphovsperson≠ | Jerome H. Friedman | Breiman, Friedman, Olshen & Stone |
| Typ≠ | Adaptive piecewise-linear regression | Recursive partitioning (if-then rules) |
| Ursprungskälla≠ | Friedman, 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 ↗ |
| Alias≠ | multivariate adaptive regression splines, earth algorithm, MARS regression, çok değişkenli uyarlamalı regresyon spline'ları | Karar Ağacı (Decision Tree), karar ağacı, classification tree, regression tree |
| Närliggande≠ | 4 | 5 |
| Sammanfattning≠ | 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 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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