AI RESEARCH
Beyond Explained Variance: A Cautionary Tale of PCA
arXiv CS.LG
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ArXi:2605.13520v1 Announce Type: cross We address shortcomings of principal component analysis (PCA) for visualizing high-dimensional data lying on a nonlinear low-dimensional manifold via two-dimensional scatterplots, focusing on a fossil teeth dataset from the early mammalian insectivore Kuehneotherium.