Title
Consensus via penalty functions for decision making in ensembles in fuzzy rule-based classification systems.
Abstract
•A consensus method via penalty functions for decision making in ensembles of fuzzy rule-based classification systems is introduced.•Overlap indices are built using overlap functions.•A method for constructing confidence and support measures from overlap indices is presented.•A new fuzzy rule mechanism is proposed, considering different overlap indices, which generalizes the classical methods.•An example of a generation of fuzzy rule-based ensembles and the decision making by consensus via penalty functions is presented.
Year
DOI
Venue
2018
10.1016/j.asoc.2017.05.050
Applied Soft Computing
Keywords
Field
DocType
Fuzzy rule-based classification system,Aggregation function,Penalty function,Overlap function,Overlap index,Confidence and support measures
Certainty,Associative property,Generalization,Fuzzy set,Association rule learning,Artificial intelligence,Mathematics,Machine learning,Penalty method,Fuzzy rule
Journal
Volume
ISSN
Citations 
67
1568-4946
16
PageRank 
References 
Authors
0.51
36
8
Name
Order
Citations
PageRank
Mikel Elkano1897.82
Mikel Galar2100340.90
José Antonio Sanz342923.40
Paula F. Schiavo4160.51
Sidnei F. Pereira Jr.5160.51
Graçaliz Pereira Dimuro666743.93
Eduardo N. Borges7324.80
Humberto Bustince81938134.10