Association Rules and Statistics

Martine Cadot 1, * Jean-Baptiste Maj 2 Tarek Ziadé
* Corresponding author
1 ABC - Machine Learning and Computational Biology
LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
2 PAROLE - Analysis, perception and recognition of speech
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : A manager would like to have a dashboard of his company without manipulating data. Usually, statistics have solved this challenge, but nowadays, data have changed (Jensen, 1992); their size has increased, and they are badly structured (Han & Kamber, 2001). A recent method—data mining—has been developed to analyze this type of data (Piatetski-Shapiro, 2000). A specific method of data mining, which fits the goal of the manager, is the extraction of association rules (Hand, Mannila & Smyth, 2001). This extraction is a part of attribute-oriented induction (Guyon & Elisseeff, 2003). The aim of this paper is to compare both types of extracted knowledge: association rules and results of statistics.
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https://hal.archives-ouvertes.fr/hal-00578418
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Submitted on : Sunday, March 20, 2011 - 11:19:34 AM
Last modification on : Thursday, January 11, 2018 - 6:21:04 AM

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Martine Cadot, Jean-Baptiste Maj, Tarek Ziadé. Association Rules and Statistics. John Wang. Encyclopedia of Data Warehousing and Mining, Information Science Reference, pp.94-97, 2009. ⟨hal-00578418⟩

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