Principal component and linear discriminant analyses for the classification of hominoid primate specimens based on bone shape data Universiteit Gent KU Leuven
In this study, we tested the hypothesis that machine learning methods can accurately classify extant primates based on triquetrum shape data. We then used this classification tool to observe the affinities between extant primates and fossil hominoids. We assessed the discrimination accuracy for an unsupervised and supervised learning pipeline, i.e. with principal component analysis (PCA) and linear discriminant analysis (LDA) feature extraction, ...