Integration of Data Mining Techniques to PostgreSQL Database Manager System
2019; Elsevier BV; Volume: 155; Linguagem: Inglês
10.1016/j.procs.2019.08.080
ISSN1877-0509
AutoresAmelec Viloria, Génesis Camargo Acuña, Daniel Jesús Alcázar Franco, Hugo Hernández Palma, Jorge Pacheco Fuentes, Etelberto Pallares Rambal,
Tópico(s)Rough Sets and Fuzzy Logic
ResumoData mining is a technique that allows to obtain patterns or models from the gathered data. This technique is applied in all kind of environments such as in the biological field, educational and financial applications, industry, police, and political processes. Within data mining there are several techniques, among which are the induction of rules and decision trees which, according to various studies carried out, are among the most used. This research analyzes decision tree data mining techniques and induction rules to integrate several of its algorithms into PostgreSQL database management system (DBMS). Through an experiment, it was found that when the algorithms are integrated to the manager, the response times and the results obtained are higher.
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