skm: Selective k-Means

Algorithms for solving selective k-means problem, which is defined as finding k rows in an m x n matrix such that the sum of each column minimal is minimized. In the scenario when m == n and each cell value in matrix is a valid distance metric, this is equivalent to a k-means problem. The selective k-means extends the k-means problem in the sense that it is possible to have m != n, often the case m < n which implies the search is limited within a small subset of rows. Also, the selective k-means extends the k-means problem in the sense that the instance in row set can be instance not seen in the column set, e.g., select 2 from 3 internet service provider (row) for 5 houses (column) such that minimize the overall cost (cell value) - overall cost is the sum of the column minimal of the selected 2 service provider.

Package details

AuthorGuang Yang
MaintainerGuang Yang <gyang274@gmail.com>
LicenseMIT + file LICENSE
Version0.1.5.4
URL http://github.com/gyang274/skm
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("skm")

Try the skm package in your browser

Any scripts or data that you put into this service are public.

skm documentation built on May 1, 2019, 10:10 p.m.