concept

Principal Component Analysis

Also known as: principal components analysis, PCA

Facts (11)

Sources

Associations between dietary diversity and self-rated health in a ... link.springer.com Springer Feb 28, 2025 4 facts

claimThe second principal component (PC2) of the dietary profile PCA correlated with '11. pulses' and '2. roots, tubers and other starchy foods', representing a gradient of complex carbohydrate sources from high fiber to high starch food items.

claimThe first principal component (PC1) of the dietary profile PCA correlated with '10. fish and shellfish' in opposition to '8. processed meat' and '7. meat', representing a gradient of animal protein sources from aquatic to terrestrial origin.

procedureTo analyze dietary data, researchers transformed a matrix of food group presence (1) or absence (0) from 24-hour recalls using Hellinger’s transformation before performing principal component analysis to account for the large number of zero values.

measurementA Principal Component Analysis (PCA) of participants’ dietary profiles based on cited food groups explained 25.05% of the variation on its two first principal components (λ1 = 0.05, λ2 = 0.04).

Adversarial testing of global neuronal workspace and ... - Nature nature.com Nature Apr 30, 2025 3 facts

claimIn the posterior cortex, Principal Component Analysis (PCA) shows clear separability between letters and false fonts at 0.3 seconds, regardless of whether the task is relevant or irrelevant.

procedureIn the study, PCA components were aligned across repetitions using Procrustes alignment and averaged together for visualization purposes.

procedureResearchers subjected the resultant representational dissimilarity matrix (RDM) to a principal component analysis (PCA) and plotted the first two dimensions against each other to produce a 2D projection of dissimilarity scores across 100 subsampling repetitions.

A comprehensive overview on demand side energy management ... link.springer.com Springer Mar 13, 2023 2 facts

claimCao et al. (2013) clustered 4000 households from the Irish CER dataset over 18 months using K-means, Self-Organizing Maps (SOM), and hierarchical clustering algorithms, utilizing distance calculations based on the 17 most significant Principal Component Analysis (PCA) components.

accountCao et al. (2013) clustered 4,000 households from the Irish CER dataset over 18 months using K-means, Self-Organizing Maps (SOM), and hierarchical clustering algorithms based on the 17 most significant Principal Component Analysis (PCA) components.

Implications of the Western Diet for Agricultural Production, Health ... frontiersin.org Frontiers 1 fact

claimPrincipal Component Analysis shows a positive correlation and similar growth rates between health issues (overweight, obesity, diabetes) and environmental variables/inputs like synthetic fertilizers.

Dietary Guidelines and Quality - Principles of Nutritional Assessment nutritionalassessment.org Arimond M, Deitchler M · nutritionalassessment.org 1 fact

referenceAnalytic approaches to defining data-driven ('a posteriori') dietary patterns include factor analysis, principal components analysis, and cluster analysis.