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Entscheidungsbaum×Generalisiertes Additives Modell (GAM)×
FachgebietMaschinelles LernenMaschinelles Lernen
FamilieMachine learningMachine learning
Entstehungsjahr19841986
UrheberBreiman, Friedman, Olshen & StoneTrevor Hastie & Robert Tibshirani
TypRecursive partitioning (if-then rules)Semi-parametric additive regression model
Wegweisende QuelleBreiman, L., Friedman, J.H., Olshen, R.A. & Stone, C.J. (1984). Classification and Regression Trees. Wadsworth. DOI ↗Hastie, T., & Tibshirani, R. (1986). Generalized additive models. Statistical Science, 1(3), 297–310. DOI ↗
AliasnamenKarar Ağacı (Decision Tree), karar ağacı, classification tree, regression treeGAM, additive model, spline-based additive regression, Genelleştirilmiş toplamsal model
Verwandt54
ZusammenfassungA 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.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.
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ScholarGateMethoden vergleichen: Decision Tree · Generalized Additive Model. Abgerufen am 2026-06-18 von https://scholargate.app/de/compare