Package: compboost
Type: Package
Title: C++ Implementation of Component-Wise Boosting
Version: 0.1.0
Authors@R: c(
  person(given = "Daniel", family = "Schalk", email = "daniel.schalk@stat.uni-muenchen.de", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-0950-1947")),
  person(given = "Janek", family = "Thomas", email = "janek.thomas@stat.uni-muenchen.de", role = "aut", comment = c(ORCID = "0000-0003-4511-6245")),
  person(given = "Bernd", family = "Bischl", email = "bernd_bischl@gmx.net", role = "aut", comment = c(ORCID = "0000-0001-6002-6980")))
Maintainer: Daniel Schalk <daniel.schalk@stat.uni-muenchen.de>
Description: C++ implementation of component-wise boosting implementation of component-wise 
  boosting written in C++ to obtain high runtime performance and full memory control. The main 
  idea is to provide a modular class system which can be extended without editing the source code. 
  Therefore, it is possible to use R functions as well as C++ functions for custom base-learners, 
  losses, logging mechanisms or stopping criteria.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Imports: Rcpp (>= 0.11.2), methods, glue, R6, checkmate
LinkingTo: Rcpp, RcppArmadillo
Suggests: RcppArmadillo (>= 0.9.100.5.0), ggplot2, testthat, rpart,
        mboost, knitr, rmarkdown, titanic, mlr, gridExtra
RcppModules: baselearner_module, compboost_module, loss_module,
        baselearner_module, baselearner_factory_module,
        baselearner_list_module, logger_module, optimizer_module,
        data_module
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-10-18 13:14:15 UTC; daniel
Author: Daniel Schalk [aut, cre] (<https://orcid.org/0000-0003-0950-1947>),
  Janek Thomas [aut] (<https://orcid.org/0000-0003-4511-6245>),
  Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>)
Repository: CRAN
Date/Publication: 2018-10-28 19:10:10 UTC
Built: R 3.5.3; x86_64-w64-mingw32; 2020-04-22 05:21:47 UTC; windows
Archs: i386, x64
