In computational learning theory, the teaching dimension of a concept class C is defined to be
is the minimum size of a witness set for c in C. Intuitively, this measures the number of instances that are needed to identify a concept in the class, using supervised learning with examples provided by a helpful teacher who is trying to convey the concept as succinctly as possible.
[2] The teaching dimension of a finite concept class can be used to give a lower and an upper bound on the membership query cost of the concept class.
In Stasys Jukna's book "Extremal Combinatorics", a lower bound is given for the teaching dimension in general: Let C be a concept class over a finite domain X.
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