CLUIN – A new method for extracting rules for large databases

Authors
Hasperué, Waldo; Corbalán, Leonardo César
Publication Year
2012
Language
English
Format
conference paper
Status
Published version
Description
When there is a need to understand the data stored in a database, one of the main requirements is being able to extract knowledge in the form of rules. Classification strategies allow extracting rules almost naturally. In this paper, the CLUHR classification strategy is extended to work with databases that have nominal attributes. Finally, the results obtained using the databases from the UCI repository are presented and compared with other existing classification models, showing that the algorithm presented requires less computational resources and achieves the same accuracy level and number of extracted rules.
Eje: Workshop Agentes y sistemas inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
Subject
Ciencias Informáticas
Access level
Open access
License
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
Repository
SEDICI (UNLP)
Institution
Universidad Nacional de La Plata
OAI Identifier
oai:sedici.unlp.edu.ar:10915/23603