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.
Package details 


Author  Guang Yang 
Maintainer  Guang Yang <[email protected]> 
License  MIT + file LICENSE 
Version  0.1.5.4 
URL  http://github.com/gyang274/skm 
Package repository  View on CRAN 
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