cata_ryebread

datasets

Hierarchical and partitioning algorithms to cluster blocks of variables. The partitioning algorithm includes an option called noise cluster to set aside atypical blocks of variables. Different thresholds per cluster can be sets. 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. The CATATIS methods allows to compute some indices and tests to control the quality of CATA data (Llobell, Bonnet & Giacalone (2024) <doi:10.1111/joss.12941>) . Multivariate analysis and clustering of subjects for quantitative multiblock data, CATA, RATA, Free Sorting and JAR experiments are available. Clustering of observations (products in sensory analysis) in multi-block context (notably with ClusMB strategy) is also included (Llobell & Giacalone (2025) <doi:10.1111/joss.70024>).Performing clustering based on CATA and liking at the same time is possible thanks to cluscata_liking function (Vigneau, Cariou, Giacalone, Berget & Llobell (2022) <doi:10.1016/j.foodqual.2021.104358>). Clustering of variables (quantitative, qualitative or mixed) can be done thanks to the MixCluStatis() function. Clustering on JAR + Liking can be achieved thanks to preprocess_JAR_liking function.

Fabien Llobell

ClustBlock

Clustering of Datasets

Evelyne Vigneau

Veronique Cariou

El Mostafa Qannari

cata_ryebread function

<p>CATA data. A data frame with 6 rows (the number of ryebread) and 1848 columns (the number of consumers (132) * the number of attributes (14)).
 For each consumer,each attribute and each product, there is 1 if the attribute has been checked by the consumer for the product, and 0 if not.</p>

Format

cata_ryebread data — cata_ryebread

cata_ryebread data

cata_ryebread: cata_ryebread data

Description

Usage

Arguments

Format

References

Examples