The Application of Clustering on Principal Components for Nutritional Epidemiology: A Workflow to Derive Dietary Patterns

The Application of Clustering on Principal Components for Nutritional Epidemiology: A Workflow to Derive Dietary Patterns

In the last decades, different multivariate techniques have been applied to multidimensional dietary datasets to identify meaningful patterns reflecting the dietary habits of populations. Among them, principal component analysis (PCA) and cluster analysis represent the two most used techniques, eith...

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Bibliographic Details
Main Authors: Andrea Maugeri, Martina Barchitta, Giuliana Favara, Claudia La Mastra, Maria Clara La Rosa, Roberta Magnano San Lio, Antonella Agodi
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Nutrients
Subjects:
diet
dietary factors
dietary dataset
nutritional epidemiology
Online Access:https://www.mdpi.com/2072-6643/15/1/195

Internet

https://www.mdpi.com/2072-6643/15/1/195

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