Model-based Boosting in R: A Hands-on Tutorial Using the R Package mboost

Hofner, Benjamin; Mayr, Andreas; Robinzonov, Nikolay und Schmid, Matthias (14. Februar 2012): Model-based Boosting in R: A Hands-on Tutorial Using the R Package mboost. Department of Statistics: Technical Reports, Nr. 120

Abstract

We provide a detailed hands-on tutorial for the R add-on package mboost. The package implements boosting for optimizing general risk functions utilizing component-wise (penalized) least squares estimates as base-learners for fitting various kinds of generalized linear and generalized additive models to potentially high-dimensional data. We give a theoretical background and demonstrate how mboost can be used to fit interpretable models of different complexity. As an example we use mboost to predict the body fat based on anthropometric measurements throughout the tutorial.

• Dokumententyp: Paper
• Keywords: boosting, component-wise functional gradient descent, generalized additive models, tutorial
• Fakultät: Mathematik, Informatik und Statistik > Statistik > Technische Reports
• Themengebiete: 500 Naturwissenschaften und Mathematik > 510 Mathematik
• Sprache: Englisch