Abstract
The different techniques used for Euclidean approximation of distances are discussed. In the special case of points in a Euclidean space, whose distances are biased due to measure errors, accepting negative eigenvalues may help in the interpretation of results that are less biased than those obtained through an additive constant solution. Numerical examples are given.
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© 1999 Springer-Verlag Berlin · Heidelberg
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Camiz, S. (1999). Comparison of Euclidean Approximations of non-Euclidean Distances. In: Vichi, M., Opitz, O. (eds) Classification and Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-60126-2_18
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DOI: https://doi.org/10.1007/978-3-642-60126-2_18
Publisher Name: Springer, Berlin, Heidelberg
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