June 2011
Beginner to intermediate
744 pages
25h 11m
English
Most association rule mining algorithms employ a support–confidence framework. Although minimum support and confidence thresholds help weed out or exclude the exploration of a good number of uninteresting rules, many of the rules generated are still not interesting to the users. Unfortunately, this is especially true when mining at low support thresholds or mining for long patterns. This has been a major bottleneck for successful application of association rule mining.
In this section, we first look at how even strong association rules can be uninteresting and misleading (Section 6.3.1). We then discuss how the support–confidence framework can be supplemented with additional interestingness ...
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