Package: subgroup.discovery
Type: Package
Title: Subgroup Discovery and Bump Hunting
Version: 0.3.1
Authors@R: c(
          person(given = "Jurian", family = "Baas", email = "j.baas@uu.nl", role = c("aut", "cre", "cph")),
          person(given = "Ad", family ="Feelders", email = "a.j.feelders@uu.nl", role = c("ctb")))
Description: Developed to assist in discovering interesting subgroups in high-dimensional data. 
  The PRIM implementation is based on the 1998 paper "Bump hunting in high-dimensional data" by Jerome H. Friedman and Nicholas I. Fisher <doi:10.1023/A:1008894516817>.
  PRIM involves finding a set of "rules" which combined imply unusually large values of some other target variable. 
  Specifically one tries to find a set of sub regions in which the target variable is substantially larger than overall mean. 
  The objective of bump hunting in general is to find regions in the input (attribute/feature) space with relatively high values for the target variable. 
  The regions are described by simple rules of the type if: condition-1 and ... and condition-n then: estimated target value. Given the data (or a subset of the data), 
  the goal is to produce a box B within which the target mean is as large as possible.
Depends: R (>= 3.6.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
URL: https://github.com/Jurian/subgroup.discovery
BugReports: https://github.com/Jurian/subgroup.discovery/issues
Date: 2020-01-27
Suggests: testthat (>= 2.1.1)
Imports: Rcpp (>= 1.0.3), RcppParallel (>= 4.4.4)
LinkingTo: Rcpp, RcppParallel, BH
SystemRequirements: GNU make, C++11
Language: en-US
NeedsCompilation: yes
Packaged: 2020-02-06 12:17:35 UTC; juria
Author: Jurian Baas [aut, cre, cph],
  Ad Feelders [ctb]
Maintainer: Jurian Baas <j.baas@uu.nl>
Repository: CRAN
Date/Publication: 2020-02-09 14:10:06 UTC
