Fuzzy interpretation of discretized intervals
When there are both numerical and nominal attributes in a database, existing data mining systems (such as rule induction and decision tree construction) discretize numerical domains into intervals and the discretized intervals are treated in a similar way to nominal values during induction. This correspondence describes a type of fuzzy intervals implemented in the HCV (Version 2.0) rule induction software (referred to as HCV hereafter) for the interpretation of rule induction results when rules with sharp intervals do not clearly apply to a test example at hand. A battery of experimental results with HCV show that these fuzzy intervals are useful.
discretization data mining fuzzy intervals rule interpretation