Learning from examples with unspecified attribute values (extended abstract)
Sally A. Goldman, Stephen S. Kwek, Stephen Scott · 1997
) Sally A. Goldman Dept. of Computer Science Washington University St. Louis, MO 63130-4899 [email protected] Stephen S. Kwek Dept. of Computer Science Washington University St. Louis, MO 63130-4899 [email protected] Stephen D. Scott Dept. of Computer Science Washington University St. Louis, MO 63130-4899 [email protected] Abstract We introduce the UAV learning model in which some of the attributes in the examples are unspecified. In our model, an example x is classified positive (resp., negative) if all possible assignments for the unspecified attributes result in a positive (resp., negative) classification. Otherwise the classification given to x is "?" (for unknown). Given an example x in which some attributes are unspecified, the oracle UAV-MQ responds with the classification of x. Given a hypothesis h, the oracle UAV-EQ returns an example x (that could have unspecified attributes) for which h(x) is incorrect. We show that any class learnable in the exact model using the...