Type: Package
Package: ODRF
Title: Oblique Decision Random Forest for Classification and Regression
Version: 0.0.3
Authors@R: c(
    person("Yu", "Liu", , "liuyuchina123@gmail.com", role = c("aut", "cre", "cph")),
    person("Yingcun", "Xia", , "staxyc@nus.edu.sg", role = "aut")
  )
Author: Yu Liu [aut, cre, cph],
  Yingcun Xia [aut]
Maintainer: Yu Liu <liuyuchina123@gmail.com>
Description: The oblique decision tree (ODT) uses linear combinations of
    predictors as partitioning variables in a decision tree. Oblique
    Decision Random Forest (ODRF) is an ensemble of multiple ODTs
    generated by feature bagging. Both can be used for classification and
    regression as supplements to the classical CART of Breiman (1984)
    <https://imsarchives.nus.edu.sg/oldwww/Programs/014swclass/files/mark.pdf>
    and Random Forest of Breiman (2001) <DOI:10.1023/A:1010933404324>
    respectively.
License: GPL (>= 3)
URL: https://liuyu-star.github.io/ODRF/
BugReports: https://github.com/liuyu-star/ODRF/issues
Depends: partykit, R (>= 3.5.0)
Imports: doParallel, foreach, glue, graphics, grid, lifecycle,
        magrittr, nnet, parallel, Pursuit, Rcpp, rlang (>= 0.4.11),
        stats
Suggests: knitr, rmarkdown, spelling, testthat (>= 3.0.0)
LinkingTo: Rcpp, RcppArmadillo
VignetteBuilder: knitr
Config/testthat/edition: 3
Encoding: UTF-8
Language: en-US
LazyData: yes
NeedsCompilation: yes
RoxygenNote: 7.2.3
Packaged: 2023-03-16 15:16:48 UTC; Administrator
Repository: CRAN
Date/Publication: 2023-03-16 16:00:02 UTC
Built: R 4.1.3; x86_64-w64-mingw32; 2023-04-17 15:26:45 UTC; windows
Archs: i386, x64
