Abstract: Principal Component Analysis (PCA) is a workhorse of modern data science. While PCA assumes the data conforms to Euclidean geometry, for specific data types, such as hierarchical and cyclic ...
Abstract: Interest in detecting networks responsible for phenotypes spans multiple scientific disciplines, including proteomics and neuroscience. Latent variable models, such as Principal Component ...
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Principal component analysis (PCA) integrates multiple clinical indicators into a single score, providing a holistic assessment. Existing clinical indicators often fail to fully reflect health ...