Partial rules: Another class of derivative and potentially uninteresting rules

A single base rule representing a fundamental inter-relationship between variables within a dataset can generate a large number of derivative rules. These are rules that appear interesting only due to the inter-relationship that is best represented by the base rule. This phenomena is well understood with respect to derivative rules formed by adding unproductive conditions to the antecedent of the base rule. We identify a new type of derivative rule that is formed by removing conditions from the antecedent of the base rule. We present statistically sound and computationally tractable techniques for detecting such rules, and experimental evidence that for some analytic tasks many such rules can be generated.