Boosting additive models using component-wise P-Splines

被引：91

作者：

Schmid, Matthias ^{[1
]}

Hothorn, Torsten ^{[2
]}

机构：

[1] Univ Erlangen Nurnberg, Inst Med Informat & Biomet & Epidemiol, D-91054 Erlangen, Germany

[2] Univ Munich, Inst Stat, D-80539 Munich, Germany

来源：

COMPUTATIONAL STATISTICS & DATA ANALYSIS | 2008年 / 53卷 / 02期

关键词：

D O I：

10.1016/j.csda.2008.09.009

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

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. (C) 2008 Elsevier B.V. All rights reserved.

引用

页码：298 / 311

页数：14

共 25 条

[1]

[Anonymous], 2006, GEN ADDITIVE MODELS

[2] Prediction games and arcing algorithms [J].

Breiman, L .

NEURAL COMPUTATION, 1999, 11 (07) :1493-1517

[3]

Breiman L, 1998, ANN STAT, V26, P801

[4] Boosting algorithms: Regularization, prediction and model fitting [J].

Buehlmann, Peter ;

Hothorn, Torsten .

STATISTICAL SCIENCE, 2007, 22 (04) :477-505

[5] Boosting with the L2 loss:: Regression and classification [J].

Bühlmann, P ;

Yu, B .

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2003, 98 (462) :324-339

[6] Boosting for high-dimensional linear models [J].

Buhlmann, Peter .

ANNALS OF STATISTICS, 2006, 34 (02) :559-583

[7]

de Boor C., 2001, A practical guide to splines

[8]

rev. ed. Applied mathematical sciences, DOI DOI 10.1007/978-1-4612-6333-3

[9] Flexible smoothing with B-splines and penalties [J].

Eilers, PHC ;

Marx, BD .

STATISTICAL SCIENCE, 1996, 11 (02) :89-102

[10]

EILERS PHC, 2004, SPLINES KNOTS UNPUB

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