%0 Journal Article %1 schmid_boosting_2008 %A Schmid, Matthias %A Hothorn, Torsten %D 2008 %J Computational Statistics & Data Analysis %K imported %N 2 %P 298--311 %R 10.1016/j.csda.2008.09.009 %T Boosting additive models using component-wise P-Splines %U http://www.sciencedirect.com/science/article/pii/S0167947308004416 %V 53 %X An efficient approximation of L 2 Boosting with component-wise smoothing splines is considered. Smoothing spline base-learners are replaced by P-spline base-learners, which yield similar prediction errors but are more advantageous from a computational point of view. A detailed analysis of the effect of various P-spline hyper-parameters on the boosting fit is given. In addition, a new theoretical result on the relationship between the boosting stopping iteration and the step length factor used for shrinking the boosting estimates is derived.

@article{schmid_boosting_2008, abstract = {An efficient approximation of L 2 Boosting with component-wise smoothing splines is considered. Smoothing spline base-learners are replaced by P-spline base-learners, which yield similar prediction errors but are more advantageous from a computational point of view. A detailed analysis of the effect of various P-spline hyper-parameters on the boosting fit is given. In addition, a new theoretical result on the relationship between the boosting stopping iteration and the step length factor used for shrinking the boosting estimates is derived.}, added-at = {2017-01-09T13:57:26.000+0100}, author = {Schmid, Matthias and Hothorn, Torsten}, biburl = {https://www.bibsonomy.org/bibtex/293c74761e08b7c9b55f9f08800ab0bc4/yourwelcome}, doi = {10.1016/j.csda.2008.09.009}, interhash = {fd337f0f0521fd8c10f530dfacb7492b}, intrahash = {93c74761e08b7c9b55f9f08800ab0bc4}, issn = {0167-9473}, journal = {Computational Statistics \& Data Analysis}, keywords = {imported}, month = dec, number = 2, pages = {298--311}, timestamp = {2017-01-09T14:01:11.000+0100}, title = {Boosting additive models using component-wise {P}-{Splines}}, url = {http://www.sciencedirect.com/science/article/pii/S0167947308004416}, urldate = {2013-06-04}, volume = 53, year = 2008 }