Data and Code: Traditional and Non-Traditional Clustering Techniques for Identifying Chrononutrition Patterns
Data and Code: Traditional and Non-Traditional Clustering Techniques for Identifying Chrononutrition Patterns
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.
This dataset accompanies a methodological paper comparing traditional and non-traditional clustering approaches for identifying chrononutrition patterns.
circadian rhythm, spectral clustering, k-means, chrononutrition, dietary patterns, gaussian mixture models, hierarchical clustering, clustering, meal timing
circadian rhythm, spectral clustering, k-means, chrononutrition, dietary patterns, gaussian mixture models, hierarchical clustering, clustering, meal timing
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