Selecting among rules induced from a hurricane database

Abstract

Rule induction can achieve orders of magnitude reduction in the volume of data descriptions. For example, we applied a commercial tool (IXLtm) to a 1,819 record tropical storm database, yielding 161 rules. However, the human comprehension goals of Knowledge Discovery in Databases may require still more orders, of magnitude. We present a rule refinement strategy, partly implemented in a Prolog program, that operationalizes interestingness into performance, simplicity, novelty, and significance. Applying the strategy to the induced rulebase yielded 10 genuinely interesting rules.