On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
Connectives and quantifiers in fuzzy sets
Fuzzy Sets and Systems - Special memorial volume on foundations of fuzzy reasoning
Fuzzy Sets and Systems
On the issue of obtaining OWA operator weights
Fuzzy Sets and Systems
An analytic approach for obtaining maximal entropy OWA operator weights
Fuzzy Sets and Systems
An overview of methods for determining OWA weights: Research Articles
International Journal of Intelligent Systems
Computers in Biology and Medicine
Expert Systems with Applications: An International Journal
OWA-weighted based clustering method for classification problem
Expert Systems with Applications: An International Journal
Classification based on fuzzy robust PCA algorithms and similarity classifier
Expert Systems with Applications: An International Journal
Sensitivity of multi-criteria decision making to linguistic quantifiers and aggregation means
Computers and Industrial Engineering
Nonlinear fuzzy robust PCA algorithms and similarity classifier in bankruptcy analysis
Expert Systems with Applications: An International Journal
Feature selection using fuzzy entropy measures with similarity classifier
Expert Systems with Applications: An International Journal
An OWA-TOPSIS method for multiple criteria decision analysis
Expert Systems with Applications: An International Journal
Decision-making in sport management based on the OWA operator
Expert Systems with Applications: An International Journal
OWA-based linkage method in hierarchical clustering: Application on phylogenetic trees
Expert Systems with Applications: An International Journal
Induced generalized intuitionistic fuzzy OWA operator for multi-attribute group decision making
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
In this article we extend the similarity classifier to cover also ordered weighted averaging (OWA) operators. Earlier, similarity classifier was mainly used with generalized mean operator, but in this article we extend this aggregation process to cover more general OWA operators. With OWA operators we concentrate on linguistic quantifier guided aggregation where several different quantifiers are studied and on how they best suite for the similarity classifier. Our proposed method is applied to real world medical data sets which are new thyroid, hypothyroid, lymphography and hepatitis data sets. Results are very promising and show improvement compared to the earlier used generalized mean operator. In this article we will show that by using OWA operators instead of generalized mean, we can improve classification accuracy with chosen data sets.