Title :
Integrating global and local boosting
Author :
Anastasia-Dimitra Lipitakis;Gerasimos S. Antzoulatos;Sotiris Kotsiantis;Michael N. Vrahatis
Author_Institution :
Department of Mathematics, University of Patras, Greece
fDate :
7/1/2015 12:00:00 AM
Abstract :
Several data analysis problems require investigations of relationships between attributes in related heterogeneous databases, where different prediction models can be more appropriate for different regions. A new technique of integrating global and local boosting is proposed. A comparison with other well known and widely used combining methods on standard benchmark datasets has shown that the proposed technique leads to more accurate results.
Keywords :
"Boosting","Classification algorithms","Training","Bagging","Databases","Decision trees"
Conference_Titel :
Information, Intelligence, Systems and Applications (IISA), 2015 6th International Conference on
DOI :
10.1109/IISA.2015.7388123