Wade Bannister

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Associative classifiers have been proposed to achieve an accurate model with each individual rule being interpretable. However, existing associative clas-sifiers often consist of a large number of rules and, thus, can be difficult to interpret. We show that associative classifiers consisting of an ordered rule set can be represented as a tree model. From(More)
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