Mining weak rules

Finding patterns from data sets is a fundamental task of data mining. If we categorize all patterns into strong, weak, and random, conventional data mining techniques are designed only to find strong patterns, which hold for numerous objects and are usually consistent with the expectations of experts. In this paper, we address the problem of finding weak patterns (i.e., reliable exceptions) from databases. They are valid for a small number of objects. A simple approach is proposed which uses deviation analysis to identify interesting exceptions and explore reliable ones. Besides, it is flexible in handling both subjective and objective exceptions. We demonstrate the effectiveness of the proposed approach through a benchmark data set.