Abstract
We present a new clustering procedure called K-midranges clustering. K-midranges is analogous to the traditional K-Means procedure for clustering interval scale data. The K-midranges procedure explicitly optimizes a loss function based on the L∞, norm (defined as the limit of an Lp norm as p approaches infinity).
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© 1998 Springer-Verlag Berlin · Heidelberg
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Carroll, J.D., Chaturvedi, A. (1998). K-midranges clustering. In: Rizzi, A., Vichi, M., Bock, HH. (eds) Advances in Data Science and Classification. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-72253-0_1
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DOI: https://doi.org/10.1007/978-3-642-72253-0_1
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