Feature Selection and Ranking Method based on Intuitionistic Fuzzy Matrix and Rough Sets

In this paper we propose a novel rough-fuzzy hybridization technique to feature selection and feature ranking problem. The idea is to model the local preference relation between pair of features by intuitionistic fuzzy values and search for a feature ranking that is consistent with those constraints...

Full description

Saved in:
Bibliographic Details
Published in2022 17th Conference on Computer Science and Intelligence Systems (FedCSIS) Vol. 30; pp. 279 - 288
Main Authors Vo, Bich Khue, Son Nguyen, Hung
Format Conference Proceeding Journal Article
LanguageEnglish
Published Polish Information Processing Society 01.01.2022
Subjects
Benchmark testing
Computer science
Decision making
Feature extraction
feature ranking
Intuitionistic fuzzy matrix
reducts
Rough sets
Online AccessGet full text
ISSN2300-5963
DOI10.15439/2022F261

Cover

More Information
Summary:In this paper we propose a novel rough-fuzzy hybridization technique to feature selection and feature ranking problem. The idea is to model the local preference relation between pair of features by intuitionistic fuzzy values and search for a feature ranking that is consistent with those constraints. We apply the techniques used in group decision making where constraints are presented in form of intuitionistic fuzzy preference relation. The proposed method has been illustrated by some simple examples and verified on a benchmark dataset.
ISSN:2300-5963
DOI:10.15439/2022F261