Fuzzy Interpretation of Induction Results

When applying rules induced from training examples to a test example, there are three possible cases which demand different actions: (1) no match, (2) single match, and (3) multiple match. Existing techniques for dealing with the first and third cases are exclusively based on probability estimation. However, when there are continuous attributes in the example space, and if these attributes have been discretised into intervals before induction, fuzzy interpretation of the discretised intervals at deduction time could be very valuable. This paper introduces the idea of using fuzzy borders for interpretation of discretised intervals at deduction time, and outlines the results we have obtained with the HCV (Version 2.0) software. Introduction Knowledge discovery in databases (KDD) is a research frontier (Wu 93a) for both database technology and machine learning techniques, and has seen sustained research over recent years. It acts as a link between the two fields, thus offering a dual be..