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This paper proves that for large bandwidths, the Gaussian RBF reproducing kernel Hilbert space becomes asymptotically isometric to Euclidean space, causing kernel PCA to converge to linear PCA. A measure of data eccentricity predicts convergence behavior in top principal directions.