Ordinal spaces

K. Keller, E. Petrov*

*Corresponding author for this work


Ordinal data analysis is an interesting direction in machinelearning. It mainly deals with data for which only the relationships ‘< ’, ‘= ’, ‘> ’between pairs of points are known. We do an attempt of formalizing structuresbehind ordinal data analysis by introducing the notion of ordinal spaces on thebase of a strict axiomatic approach. For these spaces we study general propertiesas isomorphism conditions, connections with metric spaces, embeddability inEuclidean spaces, topological properties etc.

Original languageEnglish
JournalActa Mathematica Hungarica
Issue number1
Pages (from-to)119-152
Number of pages34
Publication statusPublished - 01.02.2020


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