Subclass reachability

In computational learning theory in mathematics, given a class of concepts C, a subclass D is reachable if there exists a sample s such that D contains exactly those concepts in C that are extensions to s.[1] Not every subclass is reachable.[1]

Background

A sample is a partial function from to .[1] Identifying a concept with its characteristic function mapping to , it is a special case of a sample.[1]

Two samples are consistent if they agree on the intersection of their domains.[1] A sample extends another sample if the two are consistent and the domain of is contained in the domain of .[1]

Examples

Suppose that . Then:

  • the subclass is reachable with the sample ;[1]
  • the subclass for are reachable with a sample that maps the elements of to zero;[1]
  • the subclass , which consists of the singleton sets, is not reachable.[1]

Applications

Let be some concept class. For any concept , we call this concept -good for a positive integer if, for all , at least of the concepts in agree with on the classification of .[1] The fingerprint dimension of the entire concept class is the least positive integer such that every reachable subclass contains a concept that is -good for it.[1] This quantity can be used to bound the minimum number of equivalence queries needed to learn a class of concepts according to the following inequality:.[1]

References

  1. Angluin, D. (2004). "Queries revisited" (PDF). Theoretical Computer Science. 313 (2): 188–191.


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