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Generalized Additive Model

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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Generalized Additive Model (GAM)

Taksonoomiline meetodikirje · ml-model / machine-learning

Hastie, T., & Tibshirani, R. (1986). Generalized additive models. Statistical Science, 1(3), 297–310. · DOI 10.1214/ss/1177013604
Hastie, T. J., & Tibshirani, R. J. (1990). Generalized Additive Models. Chapman & Hall/CRC. · ISBN 978-0-412-34390-2

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Same method familyLOESSmachine-suggested · Relational suggestion, not evidence.See alsoMultiple Linear Regressionmachine-suggested · Relational suggestion, not evidence.See alsoPolynomial Regressionmachine-suggested · Relational suggestion, not evidence.Same method familyRegression Splinesmachine-suggested · Relational suggestion, not evidence.