Statistics and Its Interface
Volume 2 (2009)
Boosting on the functional ANOVA decomposition
Pages: 361 – 368
A boosting algorithm on the functional ANOVA decomposition, called ANOVA boosting, is proposed. The main idea of ANOVA boosting is to estimate each component in the functional ANOVA decomposition by combining many base (weak) learners. A regularization procedure based on the L1 penalty is proposed to give a componentwise sparse solution and an efficient computing algorithm is developed. Simulated as well as bench mark data sets are analyzed to compare ANOVA boosting and standard boosting. ANOVA boosting improves prediction accuracy as well as interpretability by estimating the components directly and providing componentwisely sparser models.
functional ANOVA decomposition, boosting, variable selection