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skm
View on CRAN: Click
here
Download and install skm package within the R console
Install from CRAN:
install.packages("skm")
Install from Github:
library("remotes")
install_github("cran/skm")
Install by package version:
library("remotes")
install_version("skm", "0.1.5.4")
Attach the package and use:
library("skm")
Maintained by
Guang Yang
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-01-23
Latest Update: 2017-01-23
Description:
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.
How to cite:
Guang Yang (2017). skm: Selective k-Means. R package version 0.1.5.4, https://cran.r-project.org/web/packages/skm. Accessed 07 Nov. 2024.
Previous versions and publish date:
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Other R packages that skm depends,
imports, suggests or enhances
Complete documentation for skm
Functions, R codes and Examples using
the skm R package
Some associated functions: col_max_idx . col_max_val . col_min_idx . col_min_val . col_rgn_val . dist_wlatlng . dist_wlatlng_cpp . skmRpl_mlp_cpp . skmSolution . skm_gdp_cpp . skm_minmax_cpp . skm_mlp_cpp . skm_mls . skm_mls_cpp . skm_rgi_cpp . skm_rgs_cpp . skm_sgl_cpp . source_zip_list . stratified_sampling . zip2012 .
Some associated R codes: RcppExports.R . Full skm package functions and examples
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