skm (0.1.5.4)

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Selective k-Means.

http://github.com/gyang274/skm
http://cran.r-project.org/web/packages/skm

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.

Maintainer: Guang Yang
Author(s): Guang Yang

License: MIT + file LICENSE

Uses: data.table, magrittr, plyr, Rcpp, RcppParallel, knitr, rmarkdown

Released 2 months ago.


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