Conference papers
From Visualization to Association Rules : an automatic approach
Abstract : The main goal of Data Mining is the research of relevant information from a huge volume of data. It is generally achieved either by automatic algorithms or by the visual exploration of data. Thanks to algorithms, an exhaustive set of patterns matching specific measures can be found. But the volume of extracted information can be greater than the volume of initial data. Visual Data Mining allows the specialist to focus on a specific area of data that may describe interesting patterns. However, it is often limited by the difficulty to deal with a great number of multi dimensional data. In this paper, we propose to mix an automatic and a manual method, by driving the automatic extraction using a data scatter plot visualization. This visualization affects the number of rules found and their construction. We illustrate our method on two databases. The first describes one month French air traffic and the second stems from 2012 KDD Cup database.
Cited literature [9 references]
https://hal-enac.archives-ouvertes.fr/hal-01078330
Contributor : Laurence Porte <>
Submitted on : Tuesday, December 16, 2014 - 5:57:19 PM
Last modification on : Thursday, May 28, 2020 - 3:46:02 PM
Document(s) archivé(s) le : Saturday, April 15, 2017 - 9:35:04 AM
Contributor : Laurence Porte <>
Submitted on : Tuesday, December 16, 2014 - 5:57:19 PM
Last modification on : Thursday, May 28, 2020 - 3:46:02 PM
Document(s) archivé(s) le : Saturday, April 15, 2017 - 9:35:04 AM
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