Exploring the data using Extended Association Rule Network

Advanced search

Search - Use quotation marks to get a more specific result

Index

Field of knowledge

Start date

Betweenand

Full text
Author(s):	de Padua, Renan ; Calcada, Dario Brito ; de Carvalho, Veronica Oliveira ; Rezende, Solange Oliveira ; IEEE Total Authors: 5
Document type:	Journal article
Source:	2018 7TH BRAZILIAN CONFERENCE ON INTELLIGENT SYSTEMS (BRACIS); v. N/A, p. 6-pg., 2018-01-01.
Abstract
In this paper, we presented the Extended Association Rule Network (ExARN) to structure, prune and analyze a set of association rules, aiming to build hypothesis candidates. The ExARN extends the ARN, proposed by [2], allowing a more complete exploration. We validate the ExARN using two databases: contact lenses and hayes-roth, both available online for download. The results were validated by comparing the ExARN to the conventional ARN and also by comparing the results with a decision tree algorithms. The approach presented promising results, showing its capability to explain a set of objective items, aiding the user on the hypothesis building. (AU)

FAPESP's process:	16/17078-0 - Mining, indexing and visualizing Big Data in clinical decision support systems (MIVisBD)
Grantee:	Agma Juci Machado Traina
Support Opportunities:	Research Projects - Thematic Grants