A computational approach to nonparametric regression: bootstrapping CMARS method

DOI10.1007/s10994-015-5502-3zbMath1343.62025OpenAlexW2143868345MaRDI QIDQ890318

Ceyda Yazıcı, İnci Batmaz, Fatma Yerlikaya Özkurt

Publication date: 10 November 2015

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10994-015-5502-3

zbMATH Keywords

machine learningwild bootstrapconic multivariate adaptive regression splinesbootstrapping regressionfixed-X resamplingrandom-X resampling

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Learning and adaptive systems in artificial intelligence (68T05)

Related Items

Model selection in multivariate adaptive regression splines (MARS) using information complexity as the fitness function, A computational approach to nonparametric regression: bootstrapping CMARS method, Estimating production functions through additive models based on regression splines, Efficient adaptive regression spline algorithms based on mapping approach with a case study on finance

Uses Software

• Matlab
• car
• Mosek
• earth
• CMARS
• ElemStatLearn
• bootstrap

Cites Work

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