Published December 2, 2025 | Version v1.0.0
Dataset Open

Data and Code: Traditional and Non-Traditional Clustering Techniques for Identifying Chrononutrition Patterns

Creators

  • 1. Universidad de Guadalajara
  • 2. Universitat Rovira i Virgili
  • 3. University of Navarra

Description

Anonymized data (n=459) and reproducible R scripts for the paper 'Traditional and Non-Traditional Clustering Techniques for Identifying Chrononutrition Patterns'. This repository implements 4 clustering methods (K-means, Hierarchical Ward, Gaussian Mixture Models, and Spectral Clustering) applied to meal timing data from Mexican university students. The analysis identifies chrononutrition patterns based on breakfast, lunch, and dinner timing.

Notes

This dataset accompanies a methodological paper comparing traditional and non-traditional clustering approaches for identifying chrononutrition patterns.

Files

jgerardomoral/chrononutrition-clustering-comparison-v1.0.0.zip

Files (67.7 kB)

Additional details

Related works

Is supplement to
Dataset: https://github.com/jgerardomoral/chrononutrition-clustering-comparison/tree/v1.0.0 (URL)

Software

Repository URL
https://github.com/jgerardomoral/chrononutrition-clustering-comparison
Programming language
R