CS 420 Lecture Notes - Lecture 3: Association Rule Learning
14 Jun 2019
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Of low-level concepts to a higher-level, more general concept set. Data can be generalized by replacing low-level concepts within the data by their corresponding higher-level concepts, or ancestors, from a concept hierarchy. The items in table 7. 1 are at the lowest level of figure 7. 2"s concept hierarchy. It is difficult to find interesting purchase patterns in such raw or primitive-level data. For instance, if dell studio xps 16 notebook or. Logitech vx nano cordless laser mouse occurs in a very small fraction of the transactions, then it can be difficult to find strong associations involving these specific items. Multilevel association rules can be mined efficiently using concept hierarchies under a support-confidence framework. For each level, any algorithm for discovering frequent itemsets may be used, such as apriori or its variations. A number of variations to this approach are: levels (referred to as uniform support): the same minimum threshold is used when mining at each abstraction level.
