2018
DOI: 10.1016/j.asoc.2017.05.050
|View full text |Cite
|
Sign up to set email alerts
|

Consensus via penalty functions for decision making in ensembles in fuzzy rule-based classification systems

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2

Citation Types

0
11
0
3

Year Published

2018
2018
2023
2023

Publication Types

Select...
5
4

Relationship

2
7

Authors

Journals

citations
Cited by 86 publications
(14 citation statements)
references
References 51 publications
0
11
0
3
Order By: Relevance
“…In recent years, two kinds of binary aggregation functions, called overlap and grouping functions respectively, were introduced by Bustince et al [8,9]. Those two functions arise from problems in image processing, decision making and classification [6,9,19,20,21,23] based on fuzzy preference relations, where the associativity property is not strongly required in reality, and thus it's not necessary to consider t-norms and t-conorms as models of operations. In image processing, for example, in 2007, scholars such as Bustince et al used the so-called restricted equivalent function to calculate the threshold value of images [6].…”
Section: Brief Overview On Overlap and Grouping Functionsmentioning
confidence: 99%
See 1 more Smart Citation
“…In recent years, two kinds of binary aggregation functions, called overlap and grouping functions respectively, were introduced by Bustince et al [8,9]. Those two functions arise from problems in image processing, decision making and classification [6,9,19,20,21,23] based on fuzzy preference relations, where the associativity property is not strongly required in reality, and thus it's not necessary to consider t-norms and t-conorms as models of operations. In image processing, for example, in 2007, scholars such as Bustince et al used the so-called restricted equivalent function to calculate the threshold value of images [6].…”
Section: Brief Overview On Overlap and Grouping Functionsmentioning
confidence: 99%
“…In image processing, for example, in 2007, scholars such as Bustince et al used the so-called restricted equivalent function to calculate the threshold value of images [6]. In decision making, in 2017, Elkano et al [21] gave a consensus method via penalty functions for decision making in ensembles of fuzzy rule based classification systems and introduced a method for constructing confidence and support measures from overlap functions. In classification, in 2015, Elkano et al [20] adapted the inference system of fuzzy association rule classification model replacing the product triangular norm with n-dimensional overlap function for high-dimensional problems.…”
Section: Brief Overview On Overlap and Grouping Functionsmentioning
confidence: 99%
“…A grouping function measures the amount of evidence in favor of either of two choices in decision making. It plays an important role in many aspects of applications such as image processing [1,3], classification [4,5], and decision making [6,7].…”
Section: Introductionmentioning
confidence: 99%
“…Overlap functions and grouping functions are two particular cases of bivariate continuous aggregation functions [4] [5]. Those two concepts have been applied to some interesting problems, for example, image processing [1] [6], classification [7] [8] and decision making [3] [9]. In recent years, some extended forms of overlap functions and grouping functions were presented, for example, n-Dimensional overlap functions and grouping functions [10], general overlap functions [11].…”
Section: Introductionmentioning
confidence: 99%