ClustBlock: Clustering of Datasets

Hierarchical and partitioning algorithms of blocks of variables. The partitioning algorithm includes an option called noise cluster to set aside atypical blocks of variables. The CLUSTATIS method (for quantitative blocks) (Llobell, Cariou, Vigneau, Labenne & Qannari (2020) <doi:10.1016/j.foodqual.2018.05.013>, Llobell, Vigneau & Qannari (2019) <doi:10.1016/j.foodqual.2019.02.017>) and the CLUSCATA method (for Check-All-That-Apply data) (Llobell, Cariou, Vigneau, Labenne & Qannari (2019) <doi:10.1016/j.foodqual.2018.09.006>, Llobell, Giacalone, Labenne & Qannari (2019) <doi:10.1016/j.foodqual.2019.05.017>) are the core of this package.

Getting started

Package details

AuthorFabien Llobell [aut, cre] (Oniris/XLSTAT), Evelyne Vigneau [ctb] (Oniris), Veronique Cariou [ctb] (Oniris), El Mostafa Qannari [ctb] (Oniris)
MaintainerFabien Llobell <>
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the ClustBlock package in your browser

Any scripts or data that you put into this service are public.

ClustBlock documentation built on April 23, 2020, 5:16 p.m.