Dynamic Ensemble Selection Based on Rough Set Reduction and Cluster Matching

2018 ◽  
Vol E101.B (10) ◽  
pp. 2196-2202
Author(s):  
Ying-Chun CHEN ◽  
Ou LI ◽  
Yu SUN
Keyword(s):  
Rough Set ◽  
Ensemble Selection ◽  
Cluster Matching ◽  
Dynamic Ensemble Selection

scholarly journals Dynamic Ensemble Selection and Data Preprocessing for Multi-Class Imbalance Learning

2019 ◽  
Vol 33 (11) ◽  
pp. 1940009
Author(s):  
Rafael M. O. Cruz ◽  
Mariana A. Souza ◽  
Robert Sabourin ◽  
George D. C. Cavalcanti
Keyword(s):  
Class Imbalance ◽  
Ensemble Methods ◽  
Data Preprocessing ◽  
Classification Problems ◽  
Ensemble Of Classifiers ◽  
Dynamic Selection ◽  
Ensemble Selection ◽  
Imbalance Learning ◽  
Class Imbalance Learning ◽  
Dynamic Ensemble Selection

Class imbalance refers to classification problems in which many more instances are available for certain classes than for others. Such imbalanced datasets require special attention because traditional classifiers generally favor the majority class which has a large number of instances. Ensemble of classifiers has been reported to yield promising results. However, the majority of ensemble methods applied to imbalance learning are static ones. Moreover, they only deal with binary imbalanced problems. Hence, this paper presents an empirical analysis of Dynamic Selection techniques and data preprocessing methods for dealing with multi-class imbalanced problems. We considered five variations of preprocessing methods and 14 Dynamic Selection schemes. Our experiments conducted on 26 multi-class imbalanced problems show that the dynamic ensemble improves the AUC and the [Formula: see text]-mean as compared to the static ensemble. Moreover, data preprocessing plays an important role in such cases.

Online pruning of base classifiers for Dynamic Ensemble Selection

2017 ◽  
Vol 72 ◽  
pp. 44-58 ◽  
Author(s):  
Dayvid V.R. Oliveira ◽  
George D.C. Cavalcanti ◽  
Robert Sabourin
Keyword(s):  
Ensemble Selection ◽  
Dynamic Ensemble Selection

scholarly journals From dynamic classifier selection to dynamic ensemble selection

2008 ◽  
Vol 41 (5) ◽  
pp. 1718-1731 ◽  
Author(s):  
Albert H.R. Ko ◽  
Robert Sabourin ◽  
Alceu Souza Britto, Jr.
Keyword(s):  
Classifier Selection ◽  
Ensemble Selection ◽  
Dynamic Classifier Selection ◽  
Dynamic Ensemble Selection
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