Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)

A PSO-based Generic Classifier Design and Weka Implementation Study

Authors
Hui Hu, Xiaodong Mao, Qin Xi
Corresponding Author
Hui Hu
Available Online March 2017.
DOI
https://doi.org/10.2991/ifmca-16.2017.4How to use a DOI?
Keywords
Classifier; PSO algorithm; Weka platform; instance-based learning.
Abstract
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.

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Volume Title
Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)
Series
Advances in Engineering Research
Publication Date
March 2017
ISBN
978-94-6252-307-4
ISSN
2352-5401
DOI
https://doi.org/10.2991/ifmca-16.2017.4How to use a DOI?
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  -