Ref: http://en.wikipedia.org/wiki/Version_space
A
version space in
concept learning or induction is the subset of all hypotheses that are
consistent with the observed training examples.
[1] This set contains all hypotheses that have not been eliminated as a result of being in conflict with observed data.
Version space for a "rectangle" hypothesis language in two dimensions.
Green pluses are positive examples, and red circles are negative
examples. GB is the maximally
general positive hypothesis boundary, and SB is the maximally
specific positive hypothesis boundary. The intermediate (thin) rectangles represent the hypotheses in the version space.
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