Hypotheses and Version Spaces

We consider the relation of a learning model described in terms of Formal Concept Analysis in [3] with a standard model of Machine Learning called version spaces. A version space consists of all possible functions compatible with training data. The overlap and distinctions of these two models are discussed. We give an algorithm how to generate a version space for which the classifiers are closed under conjunction.

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