This package implements extensions to Freund and Schapire's AdaBoost algorithm and J. Friedman's gradient boosting machine. Includes regression methods for least squares, absolute loss, logistic, Poisson, Cox proportional hazards partial likelihood, multinomial, t-distribution, AdaBoost exponential loss, Learning to Rank, and Huberized hinge loss.

Package: | gbm |

Version: | 2.1 |

Date: | 2013-05-10 |

Depends: | R (>= 2.9.0), survival, lattice, mgcv |

License: | GPL (version 2 or newer) |

URL: | http://code.google.com/p/gradientboostedmodels/ |

Index:

1 2 3 4 5 6 7 8 9 10 11 12 13 | ```
basehaz.gbm Baseline hazard function
calibrate.plot Calibration plot
gbm Generalized Boosted Regression Modeling
gbm.object Generalized Boosted Regression Model Object
gbm.perf GBM performance
plot.gbm Marginal plots of fitted gbm objects
predict.gbm Predict method for GBM Model Fits
pretty.gbm.tree Print gbm tree components
quantile.rug Quantile rug plot
relative.influence Methods for estimating relative influence
shrink.gbm L1 shrinkage of the predictor variables in a GBM
shrink.gbm.pred Predictions from a shrunked GBM
summary.gbm Summary of a gbm object
``` |

Further information is available in the following vignettes:

`gbm` | Generalized Boosted Models: A guide to the gbm package (source, pdf) |

Greg Ridgeway gregridgeway@gmail.com with contributions by Daniel Edwards, Brian Kriegler, Stefan Schroedl and Harry Southworth.

Y. Freund and R.E. Schapire (1997) “A decision-theoretic generalization of
on-line learning and an application to boosting,” *Journal of Computer and
System Sciences,* 55(1):119-139.

G. Ridgeway (1999). “The state of boosting,” *Computing Science and
Statistics* 31:172-181.

J.H. Friedman, T. Hastie, R. Tibshirani (2000). “Additive Logistic Regression:
a Statistical View of Boosting,” *Annals of Statistics* 28(2):337-374.

J.H. Friedman (2001). “Greedy Function Approximation: A Gradient Boosting
Machine,” *Annals of Statistics* 29(5):1189-1232.

J.H. Friedman (2002). “Stochastic Gradient Boosting,” *Computational Statistics
and Data Analysis* 38(4):367-378.

The MART website.

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

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