DexGroves/gbm-lrd: Generalized Boosted Regression Models
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).
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Greg Ridgeway <gregridgeway@gmail.com> with contributions from others |
| Maintainer | Harry Southworth <harry.southworth@gmail.com> |
| License | GPL (>= 2) | file LICENSE |
| Version | 2.1-06 |
| URL | https://github.com/harrysouthworth/gbm |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
|
