Transcription of Generalized Boosted Models: A guide to the gbm package
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Generalized Boosted Models: A guide to the gbm package
Generalized Boosted Models: a guide to the gbm packageGreg RidgewayAugust 3, 2007 Boosting takes on various forms with different programs using different lossfunctions, different base models, and different optimization schemes. The gbmpackage takes the approach described in [2] and [3]. Some of the terminologydiffers, mostly due to an effort to cast boosting terms into more standard sta-tistical terminology ( deviance). In addition, the gbm package implementsboosting for models commonly used in statistics but not commonly associatedwith boosting. The Cox proportional hazard model , for example, is an incred-ibly useful model and the boosting framework applies quite readily with onlyslight modification [5]. Also some algorithms implemented in the gbm packagediffer from the standard implementation. The AdaBoost algorithm [1] has aparticular loss function and a particular optimization algorithm associated withit.
Generalized Boosted Models: A guide to the gbm package Greg Ridgeway August 3, 2007 Boosting takes on various forms with different programs using different loss
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