gbm: Generalized Boosted Regression Models. 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, t-distribution loss, quantile regression, logistic, multinomial logistic, Poisson, Cox proportional hazards partial likelihood, AdaBoost exponential loss, Huberized hinge loss, and Learning to Rank measures (LambdaMart).
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- Micheletti, Natan; Foresti, Loris; Robert, Sylvain; Leuenberger, Michael; Pedrazzini, Andrea; Jaboyedoff, Michel; Kanevski, Mikhail: Machine learning feature selection methods for landslide susceptibility mapping (2014)