An implementation of extensions to Freund and Schapire's AdaBoost algorithm and Friedman's gradient boosting machine. Includes regression methods for least squares, absolute loss, tdistribution loss, quantile regression, logistic, multinomial logistic, Poisson, Cox proportional hazards partial likelihood, AdaBoost exponential loss, Huberized hinge loss, and Learning to Rank measures (LambdaMart). Originally developed by Greg Ridgeway.
Package details 


Maintainer  
License  GPL (>= 2)  file LICENSE 
Version  2.1.8 
URL  https://github.com/gbmdevelopers/gbm 
Package repository  View on GitHub 
Installation 
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