Ensemble feature selection using q-rung orthopair hesitant fuzzy Hamacher, Einstein and Dombi Aggregation operators

被引:3
|
作者
Kavitha, S. [1 ]
Janani, K. [2 ]
Mohanrasu, S. S. [2 ]
Satheeshkumar, J. [1 ]
Amudha, T. [1 ]
Rakkiyappan, R. [2 ]
机构
[1] Bharathiar Univ, Dept Comp Applicat, Coimbatore 641046, Tamil Nadu, India
[2] Bharathiar Univ, Dept Math, Coimbatore 641046, Tamil Nadu, India
关键词
Aggregation Operators; q-rung orthopair hesitant fuzzy set; Multi criteria decision making; Ensemble feature selection; Machine learning; INFORMATION AGGREGATION; DECISION-MAKING; SETS;
D O I
10.1016/j.asoc.2024.111752
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The article aims in addressing the issue of ensemble feature selection problem by modeling it as a multicriteria decision making technique. To build such a model, initially, aggregation operators such as weighted arithmetic, weighted geometric, ordered weighted arithmetic, ordered weighted geometric aggregation of Hamacher, Einstein and Dombi operators in the q-rung orthopair hesitant fuzzy environment are proposed. The properties of these operators are also discussed to provide a more elaborate understanding of them. Such an approach to ensemble feature selection has not yet been carried out in the literature which adds to the novelty of our work. Validation is provided through comparison of the performance metrics with existing and base feature selection methods and also by carrying out statistical tests. Through this article, a model for ensemble feature selection incorporating the advantages of Einstein, Hamacher, Dombi and q-rung orthopair hesitant fuzzy set was constructed which was reflected in the results.
引用
收藏
页数:38
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