Selective Ensemble Learning Method for Belief-Rule-Base Classification System Based on PAES
Traditional Belief-Rule-Based (BRB) ensemble learning methods integrate all of the trained sub-BRB systems to obtain better results than a single belief-rule-based system. However, as the number of BRB systems participating in ensemble learning increases, a large amount of redundant sub-BRB systems...
Saved in:
Main Authors: | Wanling Liu, Weikun Wu, Yingming Wang, Yanggeng Fu, Yanqing Lin |
---|---|
Format: | Article |
Language: | English |
Published: |
Tsinghua University Press
2019-12-01
|
Series: | Big Data Mining and Analytics |
Subjects: | |
Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2019.9020008 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Classification Model Based on Interval Rule Inference Network with Interpretability
by: Yunxia Zhang, et al.
Published: (2025-01-01) -
A new method for assessing the health status of aerospace equipment based on a belief rule base with balanced accuracy and complexity
by: Jinting Shen, et al.
Published: (2025-01-01) -
Greedy Algorithm for Deriving Decision Rules from Decision Tree Ensembles
by: Evans Teiko Tetteh, et al.
Published: (2025-01-01) -
Health state assessment method for complex system based on multiexpert joint belief rule base
by: Shuozi Li, et al.
Published: (2025-01-01) -
Robust Forest Sound Classification Using Pareto-Mordukhovich Optimized MFCC in Environmental Monitoring
by: Ahmad Qurthobi, et al.
Published: (2025-01-01)