Data Mining with Optimized Two-Dimensional Association Rules

摘要

We discuss data mining based on association rules for two numeric attributes and one Boolean attribute. For example, in a database of bank customers, "Age" and "Balance" are two numeric attributes, and "CardLoan" is a Boolean attribute. Taking the pair (Age, Balance) as a point in two-dimensional space, we consider an association rule of the form ((Age, Balance)∈=>(CardLoan-Yes), which implies that bank customers whose ages and balances fall within a planar region P tend to take out credit card loans with a high probability.