Package: SSLR
Type: Package
Title: Semi-Supervised Classification and Regression Methods
Version: 0.9.2
Authors@R: c(
            person("Francisco Jesús", "Palomares Alabarce", role =  c("aut", "cre"),
                                email = "fpalomares@correo.ugr.es",
                                comment = c(ORCID = "0000-0002-0499-7034")),
            person("José Manuel", "Benítez", role = "ctb",
                    email = "j.m.benitez@decsai.ugr.es",
                    comment = c(ORCID = "0000-0002-2346-0793")),
            person("Isaac", "Triguero", role = "ctb",
                    email = "isaac.triguero@nottingham.ac.uk",
                    comment = c(ORCID = "0000-0002-0150-0651")),
            person("Christoph", "Bergmeir", role = c("ctb"),
                    email = "c.bergmeir@decsai.ugr.es",
                    comment = c(ORCID = "0000-0002-3665-9021")),
             person("Mabel", "González", role = "ctb",
                    email = "mabelc@correo.ugr.es",
                    comment = c(ORCID = "0000-0003-0152-444X"))
             )
Maintainer: Francisco Jesús Palomares Alabarce <fpalomares@correo.ugr.es>
URL: https://dicits.ugr.es/software/SSLR/
Description: Providing a collection of techniques for semi-supervised 
    classification and regression. In semi-supervised problem, both labeled and unlabeled
    data are used to train a classifier. The package includes a collection of 
    semi-supervised learning techniques: self-training, co-training, democratic, 
    decision tree, random forest, 'S3VM' ... etc, with a fairly intuitive interface 
    that is easy to use.
License: GPL-3
ByteCompile: true
Depends: R (>= 2.10)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: stats, parsnip, plyr, dplyr (>= 0.8.0.1), magrittr, purrr,
        rlang (>= 0.3.1), proxy, methods, generics, utils, RANN,
        foreach, RSSL
LinkingTo: Rcpp, RcppArmadillo
Suggests: caret, tidymodels, e1071, C50, kernlab, testthat, doParallel,
        tidyverse, survival, xgboost, covr, kknn, randomForest, ranger,
        MASS, nlme, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-07-20 10:34:56 UTC; FRAJE
Author: Francisco Jesús Palomares Alabarce [aut, cre]
    (<https://orcid.org/0000-0002-0499-7034>),
  José Manuel Benítez [ctb] (<https://orcid.org/0000-0002-2346-0793>),
  Isaac Triguero [ctb] (<https://orcid.org/0000-0002-0150-0651>),
  Christoph Bergmeir [ctb] (<https://orcid.org/0000-0002-3665-9021>),
  Mabel González [ctb] (<https://orcid.org/0000-0003-0152-444X>)
Repository: CRAN
Date/Publication: 2020-07-20 11:10:02 UTC
Built: R 4.0.2; x86_64-w64-mingw32; 2020-08-02 17:10:35 UTC; windows
Archs: i386, x64
