Finding Minimal Rare Itemsets and Rare Association Rules
Identifieur interne : 003136 ( Main/Merge ); précédent : 003135; suivant : 003137Finding Minimal Rare Itemsets and Rare Association Rules
Auteurs : Laszlo Szathmary [Canada] ; Petko Valtchev [Canada] ; Amedeo Napoli [France]Source :
- Lecture Notes in Computer Science [ 0302-9743 ]
Abstract
Abstract: Rare association rules correspond to rare, or infrequent, itemsets, as opposed to frequent ones that are targeted by conventional pattern miners. Rare rules reflect regularities of local, rather than global, scope that can nevertheless provide valuable insights to an expert, especially in areas such as genetics and medical diagnosis where some specific deviations/illnesses occur only in a small number of cases. The work presented here is motivated by the long-standing open question of efficiently mining strong rare rules, i.e., rules with high confidence and low support.
Url:
DOI: 10.1007/978-3-642-15280-1_5
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<front><div type="abstract" xml:lang="en">Abstract: Rare association rules correspond to rare, or infrequent, itemsets, as opposed to frequent ones that are targeted by conventional pattern miners. Rare rules reflect regularities of local, rather than global, scope that can nevertheless provide valuable insights to an expert, especially in areas such as genetics and medical diagnosis where some specific deviations/illnesses occur only in a small number of cases. The work presented here is motivated by the long-standing open question of efficiently mining strong rare rules, i.e., rules with high confidence and low support.</div>
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