On $p$-adic Classification

Abstract

A $p$-adic modification of the split-LBG classification method is presented in which first clusterings and then cluster centers are computed which locally minimise an energy function. The outcome for a fixed dataset is independent of the prime number $p$ with finitely many exceptions. The methods are applied to the construction of $p$-adic classifiers in the context of learning.

16 pages, 7 figures, 1 table; added reference, corrected typos, minor content changes

References in corpus (3)

• Degenerating families of dendrograms
• Mumford dendrograms
• From Data to the p-Adic or Ultrametric Model

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