On $p$-adic Classification

Details On $p$-adic Classification On $p$-adic Classification

2009-03-16

arxiv.org/abs/0903.2870v2

p-Adic Numbers, Ultrametric Analysis, and Applications, Vol. 1, No. 4 (2009), 271-285

Computer Science

Learning

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

Scientific paper

10.1134/S2070046609040013

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.

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