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Boosted regression (boosting): An introductory tutorial and a Stata plugin
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DOI：10.1177/1536867X0500500304.png)
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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 R-2 value computed on a test dataset is R-2 = 21.3% for linear regression and R-2 = 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.
Keyword:
st0087
boost
boosted regression
boosting
data mining
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