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DESCRIPTION
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Package: gbm
Version: 2.2.3
Title: Generalized Boosted Regression Models
Authors@R: c(
person("Greg", "Ridgeway",
email = "gridge@upenn.edu",
role = c("aut", "cre"),
comment = c(ORCID = "0000-0001-6911-0804")),
person("Daniel", "Edwards",
email = "unknown@unknown.com",
role = "ctb"),
person("Brian", "Kriegler",
email = "bkriegler@econone.com",
role = "ctb"),
person("Stefan", "Schroedl",
email = "stefan@atomwise.com",
role = "ctb"),
person("Harry", "Southworth",
email = "harry@dataclarityconsulting.co.uk",
role = "ctb"),
person("Brandon", "Greenwell",
email = "greenwell.brandon@gmail.com",
role = "ctb",
comment = c(ORCID = "0000-0002-8120-0084")),
person("Bradley", "Boehmke",
email = "bradleyboehmke@gmail.com",
role = "ctb",
comment = c(ORCID = "0000-0002-3611-8516")),
person("Jay", "Cunningham",
email = "james@notbadafterall.com",
role = "ctb"),
person("GBM", "Developers",
role = "aut",
comment = "https://github.com/gbm-developers")
)
Depends: R (>= 2.9.0)
Imports:
lattice,
parallel,
survival
Suggests:
covr,
gridExtra,
knitr,
pdp,
RUnit,
splines,
tinytest,
vip,
viridis,
MASS
Description: 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). Originally developed by Greg Ridgeway.
Newer version available at github.com/gbm-developers/gbm3.
License: GPL (>= 2) | file LICENSE
URL: https://github.com/gbm-developers/gbm
BugReports: https://github.com/gbm-developers/gbm/issues
Encoding: UTF-8
RoxygenNote: 7.3.3
VignetteBuilder: knitr