Advances in Latent Variables Methods, Models and Applications
Maurizio Carpita ，Eugenio Brentari El，Mostafa Qannari
The Clustering of Variables around Latent Variables (CLV) approach aims to identify groups of features in a data set and, at the same time, to identify the prototype, or the latent variable, of each group. The procedure makes it possible to search for local groups or directional groups.Moreover, constraints on the latent variables may be added in order to introduce, if available, additional information about the observations and/or the variables. This approach is illustrated in two different contexts encountered in sensory analysis: (1) the clustering of sensory descriptors by taking into account their redundancy; and (2) the segmentation of a panel of consumers according to their liking, by taking into account external information about the products and the consumers.