Boosted regression (boosting): An introductory tutorial and a
Stata plugin Abstract. Boosting, or boosted regression, is a
recent data-mining technique that has shown considerable success
in predictive accuracy. This article gives an overview of
boosting and introduces a new Stata command, boost, that
implements the boosting algorithm described in Hastie,
Tibshirani, and Friedman (2001, 322). The plugin is illustrated
with a Gaussian and a logistic regression example. In the
Gaussian regression example, the R2 value computed on a test
dataset is R2 = 21.3% for linear regression and R2 = 93.8% for
boosting. In the logistic regression example, stepwise logistic
regression correctly classifies 54.1% of the observations in a
test dataset versus 76.0% for boosted logistic regression.
Currently, boost accommodates Gaussian (normal), logistic, and
Poisson boosted regression. boost is implemented as a Windows
C++ plugin. View all articles by this author: View all articles
with these keywords: boost, boosted regressio