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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).
Package details 


Author  Greg Ridgeway <[email protected]> with contributions from others 
Date of publication  20170321 06:48:03 UTC 
Maintainer  ORPHANED 
License  GPL (>= 2)  file LICENSE 
Version  2.1.3 
URL  http://code.google.com/p/gradientboostedmodels/ 
Package repository  View on CRAN 
Installation 
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