Objective Novelty of Association Rules : Measuring the Confidence Boost
نویسنده
چکیده
Résumé. On sait bien que la confiance des régles d’association n’est pas vraiment satisfaisant comme mésure d’interêt. Nous proposons, au lieu de la substituer par des autres mésures (soit, en l’employant de façon conjointe a des autres mésures), évaluer la nouveauté de chaque régle par comparaison de sa confiance par rapport á des régles plus fortes qu’on trouve au même ensemble de données. C’est á dire, on considère un seuil “relative” de confiance au lieu du seuil absolute habituel. Cette idée se précise avec la magnitude du “confidence boost”, mésurant l’increment rélative de confiance prés des régles plus fortes. Nous prouvons que nôtre proposte peut remplacer la “confidence width” et le blockage de régles employés a des publications précedentes.
منابع مشابه
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Confidence is a very natural notion to prune and rank the output of an association rule mining algorithm; however, it is well-known that merely imposing absolute confidence and support thresholds leads to certain shortcomings. Many proposals have been suggested as attempts to overcome these shortcomings. Here we propose a different alternative: to complement the association rule mining process ...
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تاریخ انتشار 2010