Vapnik-Chervonenkis Dimension and Density on Johnson and Hamming Graphs
Bjarki Geir Benediktsson, Dugald Macpherson, Isolde Adler

TL;DR
This paper investigates the VC-dimension and VC-density of the edge relation in Johnson and Hamming graphs, establishing tight bounds and demonstrating structural tameness despite their complex properties.
Contribution
The paper provides exact bounds for VC-dimension and VC-density of the edge relation on Johnson and Hamming graphs, including their induced subgraphs, revealing structural properties.
Findings
VC-dimension at most 4 for Johnson graphs and 3 for Hamming graphs, bounds are optimal.
VC-density is 2 for both Johnson and Hamming graphs.
Bounds extend to induced subgraphs and neighborhoods, indicating structural tameness.
Abstract
VC-dimension and VC-density are measures of combinatorial complexity of set systems. VC-dimension was first introduced in the context of statistical learning theory, and is tightly related to the sample complexity in PAC learning. VC-density is a refinement of VC-dimension. Both notions are also studied in model theory, in the context of \emph{dependent} theories. A set system that is definable by a formula of first-order logic with parameters has finite VC-dimension if and only if the formula is a dependent formula. In this paper we study the VC-dimension and the VC-density of the edge relation on Johnson graphs and on Hamming graphs. On a graph , the set system defined by the formula is the vertex set of along with the collection of all \emph{open neighbourhoods} of . We show that the edge relation has VC-dimension at most on Johnson graphs and at most…
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Taxonomy
TopicsComputability, Logic, AI Algorithms · Machine Learning and Algorithms · semigroups and automata theory
