A novel clustering model for three-way data concerning a set of objects on which variables are measured by different subjects is proposed. The main aim of the model is to summarize the objects through a limited number of clusters. In order to exploit the three-way structure of the data, such clusters are assumed to be common to all subjects and variables and subjects are summarized through the PARAFAC model.
Clustering models for three-way data / Vicari, Donatella; Giordani, Paolo. - (2021), pp. 432-435. (Intervento presentato al convegno 13th Scientific Meeting of the Classification and Data Analysis Group (CLADAG2021) tenutosi a Firenze; Italy (virtual conference)).
Clustering models for three-way data
Donatella Vicari;Paolo Giordani
2021
Abstract
A novel clustering model for three-way data concerning a set of objects on which variables are measured by different subjects is proposed. The main aim of the model is to summarize the objects through a limited number of clusters. In order to exploit the three-way structure of the data, such clusters are assumed to be common to all subjects and variables and subjects are summarized through the PARAFAC model.| File | Dimensione | Formato | |
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