Title
Ensemble selection with joint spectral clustering and structural sparsity
Abstract
•First unsupervised ensemble selection method with joint clustering and sparsity.•A prediction space leveraging the prediction power of an ensemble is the basis of the method.•The data in the prediction space, which globally describe the prediction distribution of the ensemble, are unlabeled.•Method’s ensemble results are robust to test instances and uses less space.
Year
DOI
Venue
2021
10.1016/j.patcog.2021.108061
Pattern Recognition
Keywords
DocType
Volume
Ensemble selection,Structural sparsity,Unsupervised selection,Spectral clustering,Dynamic and static,Robustness
Journal
119
Issue
ISSN
Citations 
1
0031-3203
1
PageRank 
References 
Authors
0.35
0
6
Name
Order
Citations
PageRank
Zhenlei Wang161.90
Suyun Zhao258520.33
Zheng Li38330.38
Hong Chen4259.84
Cuiping Li5399.19
Yufeng Shen610.35