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.
When to use the packageMost available discretization methods process one variable at a time, such as âCkmeans.1d.dpâ. 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.
To download and install the packageinstall.packages("GridOnClusters")See the Examples vignette of the package.
Citing the packageWang J, Kumar S, Song M (2020). âJoint Grid Discretization for Biological Pattern Discovery.â 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).
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