A PSO-based Generic Classifier Design and Weka Implementation Study
Hui Hu, Xiaodong Mao, Qin Xi
Available Online March 2017.
- https://doi.org/10.2991/ifmca-16.2017.4How to use a DOI?
- Classifier; PSO algorithm; Weka platform; instance-based learning.
- Aiming at dataset with different feature attributes and multi nominal decision categories, a new design algorithm using PSO for instance-based learning classifier is put forward which can facilitate to make a better classification decision. On the basis of classes and interfaces in Weka platform, this improved algorithm is implemented and added in the platform. Taking two datasets as for test cases, not only is the classifier compared with optimizing different objective functions, but also is evaluated with other classifiers. Comparisons demonstrate that the proposed algorithm can get more effective classifying results and maybe considered a generic classifier.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Hui Hu AU - Xiaodong Mao AU - Qin Xi PY - 2017/03 DA - 2017/03 TI - A PSO-based Generic Classifier Design and Weka Implementation Study BT - Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016) PB - Atlantis Press SP - 27 EP - 31 SN - 2352-5401 UR - https://doi.org/10.2991/ifmca-16.2017.4 DO - https://doi.org/10.2991/ifmca-16.2017.4 ID - Hu2017/03 ER -