Jurian/bump.hunting: Subgroup Discovery and Bump Hunting

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.

Getting started

Package details

URL https://github.com/Jurian/subgroup.discovery
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
Jurian/bump.hunting documentation built on March 24, 2020, 8:07 a.m.