ClustBlock-package

ClustBlock

<p>Hierarchical and partitioning algorithms of blocks of variables.The CLUSTATIS method and the CLUSCATA method are the core of this package</p>

clustering

Blocks

Check-All-That-Apply

Projective mapping

Sensory

Noise Cluster

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.

Fabien Llobell

Clustering of Datasets

Evelyne Vigneau

Veronique Cariou

El Mostafa Qannari

ClustBlock-package function

Clustering of Datasets — ClustBlock-package

Package:	ClustBlock
Type:	Package
Version:	2.2.0
First version Date:	2019-11-29
Last version Date:	2020-04-23

ClustBlock-package: Clustering of Datasets

Description

Arguments

Details

References