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RJcluster: A Fast Clustering Algorithm for High Dimensional Data Based on the Gram Matrix Decomposition
Clustering algorithm for high dimensional data. Assuming that P feature measurements on N objects are arranged in an N×P matrix X, this package provides clustering based on the left Gram matrix XX^T. To simulate test data, type "help('simulate_HD_data')" and to learn how to use the clustering algorithm, type "help('RJclust')". To cite this package, type 'citation("RJcluster")'.
Getting started
Browse package contents
Package details |
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| Author | Shahina Rahman [aut], Valen E. Johnson [aut], Suhasini Subba Rao [aut], Rachael Shudde [aut, cre, trl] |
| Maintainer | Rachael Shudde <rachael.shudde@gmail.com> |
| License | GPL (>= 2) |
| Version | 3.2.4 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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