Title
pClass+: A Novel Evolving Semi-Supervised Classifier
Abstract
A novel evolving semi-supervised classifier, namely Parsimonious Classifier+ (pClass+), is proposed in this paper. pClass+ enhances a recently developed classifier, namely pClass, for a semi-supervised learning scenario. As with its predecessor, pClass+ is capable of initiating its learning process from scratch with an empty rule base and adopts an open network structure, where fuzzy rules are evolved, pruned, and recalled automatically on demands. The novelty of pClass+ lies in an online active learning technique, which decreases operator’s annotation efforts and expedites its training process. pClass+ is also equipped with a new parameter identification strategy to cope with the class overlapping situation. The efficacy of pClass+ has been experimentally validated with numerous synthetic and real-world study cases, confirmed by thorough statistical tests and comparisons against state-of-the art classifiers, where pClass+ outperforms its counterparts in achieving the best trade-off between accuracy and complexity.
Year
DOI
Venue
2017
https://doi.org/10.1007/s40815-016-0236-3
International Journal of Fuzzy Systems
Keywords
Field
DocType
Evolving classifier,Semi-supervised classifier,Online learning
Active learning,Computer science,Fuzzy logic,Artificial intelligence,Operator (computer programming),Novelty,Classifier (linguistics),Margin classifier,Machine learning,Statistical hypothesis testing,Learning classifier system
Journal
Volume
Issue
ISSN
19
3
1562-2479
Citations 
PageRank 
References 
3
0.40
27
Authors
6
Name
Order
Citations
PageRank
Mahardhika Pratama170250.02
Edwin Lughofer2194099.72
Chee Peng Lim31459122.04
J. Wenny Rahayu41275106.72
Tharam S. Dillon52573340.98
Agus Budiyono63412.21