The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
The package offers a method to discretize multivariate continuous data using a grid that captures the joint distribution via preserving clusters in the original data (Wang, Kumar, and Song 2020). Joint grid discretization is applicable as a data transformation step before using other methods to infer association, function, or causality without assuming a parametric model.
Most available discretization methods process one variable at a time, such as ‘Ckmeans.1d.dp’. If discretizing each variable independently misses patterns arising from the joint distribution of multiple involved variables, one may benefit from using the joint discretization method in this package.
install.packages("GridOnClusters")See the Examples vignette of the package.
Wang J, Kumar S, Song M (2020). “Joint Grid Discretization for Biological Pattern Discovery.” In Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics. Article no. 57. doi: 10.1145/3388440.3412415 (URL: https://doi.org/10.1145/3388440.3412415).
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.