skm (0.1.5.4)
Selective kMeans.
http://github.com/gyang274/skm
http://cran.rproject.org/web/packages/skm
Algorithms for solving selective kmeans 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 kmeans problem. The selective kmeans extends the kmeans 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 kmeans extends the kmeans 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.
Maintainer:
Guang Yang
Author(s): Guang Yang
License: MIT + file LICENSE
Uses: data.table, magrittr, plyr, Rcpp, RcppParallel, knitr, rmarkdown
Released over 2 years ago.
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