Other Types of Association Mining
Contrast set learning is a form of associative learning. Contrast set learners use rules that differ meaningfully in their distribution across subsets.
Weighted class learning is another form of associative learning in which weight may be assigned to classes to give focus to a particular issue of concern for the consumer of the data mining results.
K-optimal pattern discovery provides an alternative to the standard approach to association rule learning that requires that each pattern appear frequently in the data.
Mining frequent sequences uses support to find sequences in temporal data.
Generalized Association Rules hierarchical taxonomy (concept hierarchy)
Quantitative Association Rules categorical and quantitative data
Interval Data Association Rules e.g. partition the age into 5-year-increment ranged
Maximal Association Rules
Sequential Association Rules temporal data e.g. first buy computer, then CD-Roms, then a webcam.
Read more about this topic: Association Rule Learning
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