An integrated pruning criterion for ensemble learning based on classification accuracy and diversity

Full text for this resource is not available from the Research Repository.

Fu, Bin, Wang, Zhihai, Pan, Rong, Xu, Guandong and Dolog, Peter (2013) An integrated pruning criterion for ensemble learning based on classification accuracy and diversity. In: 7th International Conference on Knowledge Management in Organizations: Service and Cloud Computing. Uden, Lorna, Herrera, Francisco, Perez, Javier Bajo and Rodriguez, Juana Manual Corchado, eds. Advances in Intelligent Systems and Computing (172). Springer Verlag, Berlin, pp. 47-58.

Dimensions Badge

Altmetric Badge

Item type Book Section
URI https://vuir.vu.edu.au/id/eprint/23985
DOI 10.1007/978-3-642-30867-3_5
Official URL http://link.springer.com/chapter/10.1007%2F978-3-6...
ISBN 9783642308666 (print) 9783642308673 (online)
Subjects Historical > FOR Classification > 0805 Distributed Computing
Historical > Faculty/School/Research Centre/Department > School of Management and Information Systems
Keywords ResPubID25880, ensemble learning, classification, ensemble pruning, diversity of classifiers
Citations in Scopus 9 - View on Scopus
Download/View statistics View download statistics for this item

Search Google Scholar

Repository staff login