In this paper, for the first time, a feature selection procedure is modeled as a multi-criteria
decision making (MCDM) process. This method is applied to a multi-label data and we have …

For the first time, the ensemble feature selection is modeled as a Multi-Criteria Decision-
Making (MCDM) process in this paper. For this purpose, we used the VIKOR method as a …

Abstract Ant Colony Optimization (ACO) is a probabilistic and approximation metaheuristic
algorithm to solve complex combinatorial optimization problems. ACO algorithm is inspired …

Multi-label learning algorithms have significant challenges due to high-dimensional feature
space and noises in multi-label datasets. Feature selection methods are effective techniques …

The deformation of a Geosynthetic reinforced soil (GRS) structure is a key factor in designing
this type of retaining structures. On the other hand, the feasibility of artificial intelligence …

This paper proposed a Multi-Criteria Decision-Making (MCDM) modeling to deal with multi-
target regression problem. This model offered a feature ranking approach for multi-target …

Abstract Wireless Sensor Networks (WSNs) are the main component in the Internet of Things
(IoT) and smart cities to sense our environment, gather essential and meaningful data, and …

In this paper, ensemble feature selection is modeled as a bi-objective optimization problem
regarding features' relevancy and redundancy degree. The proposed method, which is …

Many real-world data have multiple class labels known as multi-label data, where the labels
are correlated with each other, and as such, they are not independent. Since these data are …

Researchers have considered multi-label learning because of its presence in various real-
world applications, in which each entity is associated with more than one class label. Since …